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  • 1.
    Adaldo, Antonio
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Liuzza, Davide
    Univ Sannio, Dept Engn, I-82100 Benevento, Italy..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Cloud-Supported Formation Control of Second-Order Multiagent Systems2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 4, p. 1563-1574Article in journal (Refereed)
    Abstract [en]

    This paper addresses a formation problem for a network of autonomous agents with second-order dynamics and bounded disturbances. Coordination is achieved by having the agents asynchronously upload (download) data to (from) a shared repository, rather than directly exchanging data with other agents. Well-posedness of the closed-loop system is demonstrated by showing that there exists a lower bound for the time interval between two consecutive agent accesses to the repository. Numerical simulations corroborate the theoretical results.

  • 2. Ahmed, J.
    et al.
    Josefsson, T.
    Johnsson, A.
    Flinta, C.
    Moradi, F.
    Pasquini, R.
    Stadler, Rolf
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Automated diagnostic of virtualized service performance degradation2018In: IEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 1-9Conference paper (Refereed)
    Abstract [en]

    Service assurance for cloud applications is a challenging task and is an active area of research for academia and industry. One promising approach is to utilize machine learning for service quality prediction and fault detection so that suitable mitigation actions can be executed. In our previous work, we have shown how to predict service-level metrics in real-time just from operational data gathered at the server side. This gives the service provider early indications on whether the platform can support the current load demand. This paper provides the logical next step where we extend our work by proposing an automated detection and diagnostic capability for the performance faults manifesting themselves in cloud and datacenter environments. This is a crucial task to maintain the smooth operation of running services and minimizing downtime. We demonstrate the effectiveness of our approach which exploits the interpretative capabilities of Self- Organizing Maps (SOMs) to automatically detect and localize different performance faults for cloud services. © 2018 IEEE.

  • 3.
    Al Ahad, Muhammed Abdullah
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Simmendinger, Christian
    T Syst Solut Res GmbH, D-70563 Stuttgart, Germany..
    Iakymchuk, Roman
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Laure, Erwin
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Markidis, Stefano
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Efficient Algorithms for Collective Operations with Notified Communication in Shared Windows2018In: PROCEEDINGS OF PAW-ATM18: 2018 IEEE/ACM PARALLEL APPLICATIONS WORKSHOP, ALTERNATIVES TO MPI (PAW-ATM), IEEE , 2018, p. 1-10Conference paper (Refereed)
    Abstract [en]

    Collective operations are commonly used in various parts of scientific applications. Especially in strong scaling scenarios collective operations can negatively impact the overall applications performance: while the load per rank here decreases with increasing core counts, time spent in e.g. barrier operations will increase logarithmically with the core count. In this article, we develop novel algorithmic solutions for collective operations such as Allreduce and Allgather(V)-by leveraging notified communication in shared windows. To this end, we have developed an extension of GASPI which enables all ranks participating in a shared window to observe the entire notified communication targeted at the window. By exploring benefits of this extension, we deliver high performing implementations of Allreduce and Allgather(V) on Intel and Cray clusters. These implementations clearly achieve 2x-4x performance improvements compared to the best performing MPI implementations for various data distributions.

  • 4.
    Beckman, Claes
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Center for Wireless Systems, Wireless@kth.
    Examining the performance of dul band base station antennas: What progress is being made?1996In: Integrating GSM & DCS 1800: Exploiting the business potential of, London: IIR , 1996Conference paper (Other (popular science, discussion, etc.))
    Abstract [en]

    The recent growth in cellular communications has rapidly created a need for more radio channels. In order to make better use of the available frequency bands new access techniques such as TDMA (Time Division Multiple Access), FDMA (Frequency DMA) and CDMA (Code DMA) have been introduced. Still, the need for new channels is strong and new frequency bands have therefore been allocated for future wireless communication systems. These new communication systems, e.g. the European Personal Communication Network (PCN: 1710-1880MHz) and the North American Personal Communication System (PCS: 1850-1990MHz), use frequencies about twice as high as their predecessors (e.g. AMPS: 824-894MHz and GSM: 880-960MHz). However, at a time when our downtown areas already are littered with basestation antennas, operators are not keen to install more. Therefore, dual-band antennas have gained an increased interest. They would allow the operators to replace two antennas for separate frequency bands with one only, thus, reducing the windload of the towers and perhaps most importantly reducing the cost of installation.

  • 5.
    Beckman, Claes
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Center for Wireless Systems, Wireless@kth.
    Svar till PTS konsultation inför planerad tilldelning av frekvensutrymme i 2,3- och 3,5 GHz-banden samt tilldelning av frekvensutrymme för lokala tillstånd2019Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    KTH, Skolan för elektroteknik och datavetenskap (EECS) har beretts möjlighet att ge sin syn på PTS ”Konsultation inför planerad tilldelning av frekvensutrymme i 2,3- och 3,5 GHz-banden samt tilldelning av frekvensutrymme för lokala tillstånd”, PTS DNR 18-8496.

    KTH anser att det är olyckligt att PTS frångår principen om teknikneutrala band. Vi förstår att i detta fall finns inga alternativ men råder PTS att arbeta för att framtida spektrumtilldelning sker på teknikneutral basis då inlåsning av frekvensband till specifika tekniker inte bidrar till innovation.

    TDD medger ett mer effektivt utnyttjande av spektrum i fallet då nedlänkstrafik dominerar. Denna vinst måste dock vägas mot det faktum att co-ordinering och synkronisering av och mellan operatörernas nät hämmar konkurrensen. En möjlig framtida lösning är att 3.5 bandet enbart används för nedlänk och att upplänk sker i annat band (tex 1800 bandet). 

    Slutligen så bör spektrumvillkoren vara oberoende av de nu existerande aktörerna. För att även öppna upp för flera och ev nya operatörer så föreslår vi att hela bandet 3,4 - 3,8GHz bjuds ut vid denna auktion.

  • 6.
    Brucker, Manuel
    et al.
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany..
    Durner, Maximilian
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany..
    Ambrus, Rares
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Marton, Zoltan Csaba
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany..
    Wendt, Axel
    Robert Bosch, Corp Res, St Joseph, MI USA.;Robert Bosch, Corp Res, Gerlingen, Germany..
    Jensfelt, Patric
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Arras, Kai O.
    Robert Bosch, Corp Res, St Joseph, MI USA.;Robert Bosch, Corp Res, Gerlingen, Germany..
    Triebel, Rudolph
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany.;Tech Univ Munich, Dep Comp Sci, Munich, Germany..
    Semantic Labeling of Indoor Environments from 3D RGB Maps2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE Computer Society, 2018, p. 1871-1878Conference paper (Refereed)
    Abstract [en]

    We present an approach to automatically assign semantic labels to rooms reconstructed from 3D RGB maps of apartments. Evidence for the room types is generated using state-of-the-art deep-learning techniques for scene classification and object detection based on automatically generated virtual RGB views, as well as from a geometric analysis of the map's 3D structure. The evidence is merged in a conditional random field, using statistics mined from different datasets of indoor environments. We evaluate our approach qualitatively and quantitatively and compare it to related methods.

  • 7.
    Båberg, Fredrik
    et al.
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Petter, Ögren
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Formation Obstacle Avoidance using RRT and Constraint Based Programming2017In: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), IEEE conference proceedings, 2017, article id 8088131Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a new way of doing formation obstacle avoidance using a combination of Constraint Based Programming (CBP) and Rapidly Exploring Random Trees (RRTs). RRT is used to select waypoint nodes, and CBP is used to move the formation between those nodes, reactively rotating and translating the formation to pass the obstacles on the way. Thus, the CBP includes constraints for both formation keeping and obstacle avoidance, while striving to move the formation towards the next waypoint. The proposed approach is compared to a pure RRT approach where the motion between the RRT waypoints is done following linear interpolation trajectories, which are less computationally expensive than the CBP ones. The results of a number of challenging simulations show that the proposed approach is more efficient for scenarios with high obstacle densities.

  • 8.
    Carvalho, Joao Frederico
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Vejdemo-Johansson, Mikael
    CUNY College of Staten Island, Mathematics Department, New York, USA.
    Kragic, Danica
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Pokorny, Florian T.
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Path Clustering with Homology Area2018In: 2018 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2018, p. 7346-7353Conference paper (Refereed)
    Abstract [en]

    Path clustering has found many applications in recent years. Common approaches to this problem use aggregates of the distances between points to provide a measure of dissimilarity between paths which do not satisfy the triangle inequality. Furthermore, they do not take into account the topology of the space where the paths are embedded. To tackle this, we extend previous work in path clustering with relative homology, by employing minimum homology area as a measure of distance between homologous paths in a triangulated mesh. Further, we show that the resulting distance satisfies the triangle inequality, and how we can exploit the properties of homology to reduce the amount of pairwise distance calculations necessary to cluster a set of paths. We further compare the output of our algorithm with that of DTW on a toy dataset of paths, as well as on a dataset of real-world paths.

  • 9. Chien, Steven W. D.
    et al.
    Markidis, Stefano
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Sishtla, Chaitanya Prasad
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Santos, Luis
    Herman, Pawel
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Nrasimhamurthy, Sai
    Laure, Erwin
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Characterizing Deep-Learning I/O Workloads in TensorFlow2018In: Proceedings of PDSW-DISCS 2018: 3rd Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems, Held in conjunction with SC 2018: The International Conference for High Performance Computing, Networking, Storage and Analysis, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 54-63Conference paper (Refereed)
    Abstract [en]

    The performance of Deep-Learning (DL) computing frameworks rely on the rformance of data ingestion and checkpointing. In fact, during the aining, a considerable high number of relatively small files are first aded and pre-processed on CPUs and then moved to accelerator for mputation. In addition, checkpointing and restart operations are rried out to allow DL computing frameworks to restart quickly from a eckpoint. Because of this, I/O affects the performance of DL plications. this work, we characterize the I/O performance and scaling of nsorFlow, an open-source programming framework developed by Google and ecifically designed for solving DL problems. To measure TensorFlow I/O rformance, we first design a micro-benchmark to measure TensorFlow ads, and then use a TensorFlow mini-application based on AlexNet to asure the performance cost of I/O and checkpointing in TensorFlow. To prove the checkpointing performance, we design and implement a burst ffer. find that increasing the number of threads increases TensorFlow ndwidth by a maximum of 2.3 x and 7.8 x on our benchmark environments. e use of the tensorFlow prefetcher results in a complete overlap of mputation on accelerator and input pipeline on CPU eliminating the fective cost of I/O on the overall performance. The use of a burst ffer to checkpoint to a fast small capacity storage and copy ynchronously the checkpoints to a slower large capacity storage sulted in a performance improvement of 2.6x with respect to eckpointing directly to slower storage on our benchmark environment.

  • 10.
    Chien, Steven Wei Der
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Sishtla, Chaitanya Prasad
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Markidis, Stefano
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Jun, Zhang
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Peng, Ivy Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC. KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Laure, Erwin
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC. KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    An Evaluation of the TensorFlow Programming Model for Solving Traditional HPC Problems2018In: Proceedings of the 5th International Conference on Exascale Applications and Software, The University of Edinburgh , 2018, p. 34-Conference paper (Refereed)
    Abstract [en]

    Computational intensive applications such as pattern recognition, and natural language processing, are increasingly popular on HPC systems. Many of these applications use deep-learning, a branch of machine learning, to determine the weights of artificial neural network nodes by minimizing a loss function. Such applications depend heavily on dense matrix multiplications, also called tensorial operations. The use of Graphics Processing Unit (GPU) has considerably speeded up deep-learning computations, leading to a Renaissance of the artificial neural network. Recently, the NVIDIA Volta GPU and the Google Tensor Processing Unit (TPU) have been specially designed to support deep-learning workloads. New programming models have also emerged for convenient expression of tensorial operations and deep-learning computational paradigms. An example of such new programming frameworks is TensorFlow, an open-source deep-learning library released by Google in 2015. TensorFlow expresses algorithms as a computational graph where nodes represent operations and edges between nodes represent data flow. Multi-dimensional data such as vectors and matrices which flows between operations are called Tensors. For this reason, computation problems need to be expressed as a computational graph. In particular, TensorFlow supports distributed computation with flexible assignment of operation and data to devices such as GPU and CPU on different computing nodes. Computation on devices are based on optimized kernels such as MKL, Eigen and cuBLAS. Inter-node communication can be through TCP and RDMA. This work attempts to evaluate the usability and expressiveness of the TensorFlow programming model for traditional HPC problems. As an illustration, we prototyped a distributed block matrix multiplication for large dense matrices which cannot be co-located on a single device and a Conjugate Gradient (CG) solver. We evaluate the difficulty of expressing traditional HPC algorithms using computational graphs and study the scalability of distributed TensorFlow on accelerated systems. Our preliminary result with distributed matrix multiplication shows that distributed computation on TensorFlow is extremely scalable. This study provides an initial investigation of new emerging programming models for HPC.

  • 11.
    Chien, Wei Der
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    An Evaluation of TensorFlow as a Programming Framework for HPC Applications2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In recent years, deep-learning, a branch of machine learning gained increasing popularity due to their extensive applications and performance. At the core of these application is dense matrix-matrix multiplication. Graphics Processing Units (GPUs) are commonly used in the training process due to their massively parallel computation capabilities. In addition, specialized low-precision accelerators have emerged to specifically address Tensor operations. Software frameworks, such as TensorFlow have also emerged to increase the expressiveness of neural network model development. In TensorFlow computation problems are expressed as Computation Graphs where nodes of a graph denote operation and edges denote data movement between operations. With increasing number of heterogeneous accelerators which might co-exist on the same cluster system, it became increasingly difficult for users to program efficient and scalable applications. TensorFlow provides a high level of abstraction and it is possible to place operations of a computation graph on a device easily through a high level API. In this work, the usability of TensorFlow as a programming framework for HPC application is reviewed. We give an introduction of TensorFlow as a programming framework and paradigm for distributed computation. Two sample applications are implemented on TensorFlow: tiled matrix multiplication and conjugate gradient solver for solving large linear systems. We try to illustrate how such problems can be expressed in computation graph for distributed computation. We perform scalability tests and comment on performance scaling results and quantify how TensorFlow can take advantage of HPC systems by performing micro-benchmarking on communication performance. Through this work, we show that TensorFlow is an emerging and promising platform which is well suited for a particular class of problem which requires very little synchronization.

  • 12.
    Colombo, Leonardo
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Clark, W.
    Bloch, A.
    Time reversal symmetries and zero dynamics for simple hybrid Hamiltonian control systems2018In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 2218-2223Conference paper (Refereed)
    Abstract [en]

    This paper studies Hamel's formalism for simple hybrid mechanical control systems and explores the role of time-reversal symmetries and hybrid zero dynamics to predict the existence of periodic orbits in these control system. A time reversal symmetry in the phase-space permits us to construct a time reversible hybrid Hamiltonian system. If the Hamiltonian function describing the continuous dynamics and the impact map are invariants under a time reversal symmetry on the zero hybrid dynamics, under some mild conditions, we find sufficient conditions for the existence of periodic solutions for the class of simple hybrid Hamiltonian control systems.

  • 13.
    Colombo, Leonardo
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Optimal Control of Left-Invariant Multi-Agent Systems with Asymmetric Formation Constraints2018In: 2018 European Control Conference, ECC 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1728-1733, article id 8550238Conference paper (Refereed)
    Abstract [en]

    In this work we study an optimal control problem for a multi-agent system modeled by an undirected formation graph with nodes describing the kinematics of each agent, given by a left invariant control system on a Lie group. The agents should avoid collision between them in the workspace. Such a task is done by introducing some potential functions into the cost functional for the optimal control problem, corresponding to fictitious forces, induced by the formation constraint among agents, that break the symmetry of the individual agents and the cost functions, and rendering the optimal control problem partially invariant by a Lie group of symmetries. Reduced necessary conditions for the existence of normal extremals are obtained using techniques of variational calculus on manifolds. As an application we study an optimal control problem for multiple unicycles.

  • 14. Dai, L.
    et al.
    Gao, Yulong
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xie, L.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xia, Y.
    Stochastic self-triggered model predictive control for linear systems with probabilistic constraints2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 92, p. 9-17Article in journal (Refereed)
    Abstract [en]

    A stochastic self-triggered model predictive control (SSMPC) algorithm is proposed for linear systems subject to exogenous disturbances and probabilistic constraints. The main idea behind the self-triggered framework is that at each sampling instant, an optimization problem is solved to determine both the next sampling instant and the control inputs to be applied between the two sampling instants. Although the self-triggered implementation achieves communication reduction, the control commands are necessarily applied in open-loop between sampling instants. To guarantee probabilistic constraint satisfaction, necessary and sufficient conditions are derived on the nominal systems by using the information on the distribution of the disturbances explicitly. Moreover, based on a tailored terminal set, a multi-step open-loop MPC optimization problem with infinite prediction horizon is transformed into a tractable quadratic programming problem with guaranteed recursive feasibility. The closed-loop system is shown to be stable. Numerical examples illustrate the efficacy of the proposed scheme in terms of performance, constraint satisfaction, and reduction of both control updates and communications with a conventional time-triggered scheme.

  • 15. Dai, L.
    et al.
    Xia, Y.
    Gao, Yulong
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Cannon, M.
    Distributed stochastic MPC for systems with parameter uncertainty and disturbances2018In: International Journal of Robust and Nonlinear Control, ISSN 1049-8923, E-ISSN 1099-1239, Vol. 28, no 6, p. 2424-2441Article in journal (Refereed)
    Abstract [en]

    A distributed stochastic model predictive control algorithm is proposed for multiple linear subsystems with both parameter uncertainty and stochastic disturbances, which are coupled via probabilistic constraints. To handle the probabilistic constraints, the system dynamics is first decomposed into a nominal part and an uncertain part. The uncertain part is further divided into 2 parts: the first one is constrained to lie in probabilistic tubes that are calculated offline through the use of the probabilistic information on disturbances, whereas the second one is constrained to lie in polytopic tubes whose volumes are optimized online and whose facets' orientations are determined offline. By permitting a single subsystem to optimize at each time step, the probabilistic constraints are then reduced into a set of linear deterministic constraints, and the online optimization problem is transformed into a convex optimization problem that can be performed efficiently. Furthermore, compared to a centralized control scheme, the distributed stochastic model predictive control algorithm only requires message transmissions when a subsystem is optimized, thereby offering greater flexibility in communication. By designing a tailored invariant terminal set for each subsystem, the proposed algorithm can achieve recursive feasibility, which, in turn, ensures closed-loop stability of the entire system. A numerical example is given to illustrate the efficacy of the algorithm. Copyright 

  • 16. Danglot, Benjamin
    et al.
    Preux, Philippe
    Baudry, Benoit
    Monperrus, Martin
    KTH, School of Electrical Engineering and Computer Science (EECS), Theoretical Computer Science, TCS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Advanced Software Technology Research (CASTOR).
    Correctness attraction: a study of stability of software behavior under runtime perturbation2018In: Journal of Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 23, no 4, p. 2086-2119Article in journal (Refereed)
    Abstract [en]

    Can the execution of software be perturbed without breaking the correctness of the output? In this paper, we devise a protocol to answer this question from a novel perspective. In an experimental study, we observe that many perturbations do not break the correctness in ten subject programs. We call this phenomenon “correctness attraction”. The uniqueness of this protocol is that it considers a systematic exploration of the perturbation space as well as perfect oracles to determine the correctness of the output. To this extent, our findings on the stability of software under execution perturbations have a level of validity that has never been reported before in the scarce related work. A qualitative manual analysis enables us to set up the first taxonomy ever of the reasons behind correctness attraction.

  • 17.
    Demirel, Burak
    et al.
    Paderborn Univ, Chair Automat Control EIME, D-33098 Paderborn, Germany..
    Ghadimi, Euhanna
    Huawei Technol Sweden AB, SE-16494 Kista, Sweden..
    Quevedo, Daniel E.
    Paderborn Univ, Chair Automat Control EIME, D-33098 Paderborn, Germany..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Optimal Control of Linear Systems With Limited Control Actions: Threshold-Based Event-Triggered Control2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 3, p. 1275-1286Article in journal (Refereed)
    Abstract [en]

    We consider a finite-horizon linear-quadratic optimal control problem where only a limited number of control messages are allowed for sending from the controller to the actuator. To restrict the number of control actions computed and transmitted by the controller, we employ a threshold-based event-triggering mechanism that decides whether or not a control message needs to be calculated and delivered. Due to the nature of threshold-based event-triggering algorithms, finding the optimal control sequence requires minimizing a quadratic cost function over a nonconvex domain. In this paper, we first provide an exact solution to this nonconvex problem by solving an exponential number of quadratic programs. To reduce computational complexity, we then propose two efficient heuristic algorithms based on greedy search and the alternating direction method of multipliers technique. Later, we consider a receding horizon control strategy for linear systems controlled by event-triggered controllers, and we further provide a complete stability analysis of receding horizon control that uses finite-horizon optimization in the proposed class. Numerical examples testify to the viability of the presented design technique.

  • 18.
    Du, Wen
    et al.
    Univ North Texas, Dept Elect Engn, Denton, TX 76203 USA..
    Yi, Xinlei
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    George, Jemin
    US Army Res Lab, Adelphi, MD 20783 USA..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Yang, Tao
    Univ North Texas, Dept Elect Engn, Denton, TX 76203 USA..
    Distributed Optimization with Dynamic Event-Triggered Mechanisms2018In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 969-974Conference paper (Refereed)
    Abstract [en]

    In this paper, we consider the distributed optimization problem, whose objective is to minimize the global objective function, which is the sum of local convex objective functions, by using local information exchange. To avoid continuous communication among the agents, we propose a distributed algorithm with a dynamic event-triggered communication mechanism. We show that the distributed algorithm with the dynamic event-triggered communication scheme converges to the global minimizer exponentially, if the underlying communication graph is undirected and connected. Moreover, we show that the event-triggered algorithm is free of Zeno behavior. For a particular case, we also explicitly characterize the lower bound for inter-event times. The theoretical results are illustrated by numerical simulations.

  • 19.
    Duberg, Daniel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Jensfelt, Patric
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    The Obstacle-restriction Method for Tele-operation of Unmanned Aerial Vehicles with Restricted Motion2018In: 2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), IEEE , 2018, p. 266-273Conference paper (Refereed)
    Abstract [en]

    This paper presents a collision avoidance method for tele-operated unmanned aerial vehicles (UAVs). The method is designed to assist the operator at all times, such that the operator can focus solely on the main objectives instead of avoiding obstacles. We restrict the altitude to be fixed in a three dimensional environment to simplify the control and operation of the UAV. The method contributes a number of desired properties not found in other collision avoidance systems for tele-operated UAVs. Our method i) can handle situations where there is no input from the user by actively stopping and proceeding to avoid obstacles, ii) allows the operator to slide between prioritizing staying away from objects and getting close to them in a safe way when so required, and iii) provides for intuitive control by not deviating too far from the control input of the operator. We demonstrate the effectiveness of the method in real world experiments with a physical hexacopter in different indoor scenarios. We also present simulation results where we compare controlling the UAV with and without our method activated.

  • 20.
    Dugani, Vishwanath
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC. KTH, School of Computer Science and Communication (CSC).
    Continuous system-wide profiling of High Performance Computing parallel applications: Profiling high performance applications2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Profiling of an application identifies parts of the code being executed using the hardware performance counters thus providing the application’s performance. Profiling has long been standard in the development process focused on a single execution of a single program. As computing systems have evolved, understanding the bigger picture across multiple machines has become increasingly important. As supercomputing grows in pervasiveness and scale, understanding parallel applications performance and utilization characteristics is critically important, because even minor performance improvements translate into large cost savings. The study surveys various tools for the application. After which, Perfminer was integrated in SCANIA’s Linux clusters to profile CFD and FEA applications exploiting the batch queue system features for continuous system wide profiling, which provides performance insights for high performance applications, with negligible overhead. Perfminer provides stable, accurate profiles and a cluster-scale tool for performance analysis. Perfminer effectively highlights the micro-architectural bottlenecks.

  • 21.
    Dyczynski, Matheus
    et al.
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    Yu, Yasmin
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden.;Sprint Biosci, Huddinge, Sweden..
    Otrocka, Magdalena
    Karolinska Inst, Dept Med Biochem & Biophys, Sci Life Lab Stockholm, Chem Biol Consortium Sweden, Solna, Sweden..
    Parpal, Santiago
    Sprint Biosci, Huddinge, Sweden..
    Braga, Tiago
    Sprint Biosci, Huddinge, Sweden..
    Henley, Aine Brigette
    Sprint Biosci, Huddinge, Sweden..
    Zazzi, Henric
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Lerner, Mikael
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    Wennerberg, Krister
    Univ Helsinki, Inst Mol Med Finland, FIMM, Helsinki, Finland..
    Viklund, Jenny
    Sprint Biosci, Huddinge, Sweden..
    Martinsson, Jessica
    Sprint Biosci, Huddinge, Sweden..
    Grander, Dan
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    De Milito, Angelo
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden.;Sprint Biosci, Huddinge, Sweden..
    Tamm, Katja Pokrovskaja
    Karolinska Inst, Dept Oncol Pathol, Canc Ctr Karolinska, Stockholm, Sweden..
    Targeting autophagy by small molecule inhibitors of vacuolar protein sorting 34 (Vps34) improves the sensitivity of breast cancer cells to Sunitinib2018In: Cancer Letters, ISSN 0304-3835, E-ISSN 1872-7980, Vol. 435, p. 32-43Article in journal (Refereed)
    Abstract [en]

    Resistance to chemotherapy is a challenging problem for treatment of cancer patients and autophagy has been shown to mediate development of resistance. In this study we systematically screened a library of 306 known anti-cancer drugs for their ability to induce autophagy using a cell-based assay. 114 of the drugs were classified as autophagy inducers; for 16 drugs, the cytotoxicity was potentiated by siRNA-mediated knock-down of Atg7 and Vps34. These drugs were further evaluated in breast cancer cell lines for autophagy induction, and two tyrosine kinase inhibitors, Sunitinib and Erlotinib, were selected for further studies. For the pharmacological inhibition of autophagy, we have characterized here a novel highly potent selective inhibitor of Vps34, SB02024. SB02024 blocked autophagy in vitro and reduced xenograft growth of two breast cancer cell lines, MDA-MB-231 and MCF-7, in vivo. Vps34 inhibitor significantly potentiated cytotoxicity of Sunitinib and Erlotinib in MCF-7 and MDA-MB-231 in vitro in monolayer cultures and when grown as multicellular spheroids. Our data suggests that inhibition of autophagy significantly improves sensitivity to Sunitinib and Erlotinib and that Vps34 is a promising therapeutic target for combination strategies in breast cancer.

  • 22.
    Eklund, Frida
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Visualisation - Interaction - Collaboration, VIC.
    Make people move: Utilizing smartphone motion sensors to capture physical activity within audiences during lectures2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    It takes only about 10-30 minutes into a sedentary lecture before audience attention is decreasing. There are different ways to avoid this. One is to use a web-based audience response systems (ARS), where the audience interact with the lecturer through their smartphones, and another is to take short breaks, including physical movements, to re-energize both the body and the brain.

    In this study, these two methods have been combined and explored. By utilizing the motion sensors that are integrated in almost every smartphone, a physical activity for a lecture audience was created and implemented in the ARS platform Mentimeter. The proof of concept was evaluated in two lectures, based on O’Brien and Toms' model of engagement. The aim was to explore the prerequisites, both in terms of design and implementation, for creating an engaging physical activity within a lecture audience, using smartphone motion sensors to capture movements and a web-based ARS to present the data.

    The results showed that the proof of concept was perceived as fun and engaging, where important factors for creating engagement were found to be competition and a balanced level of task difficulty. The study showed that feedback is complicated when it comes to motion gesture interactions, and that there are limitations as to what can be done with smartphone motion sensors using web technologies. There is great potential for further research in how to design an energizing lecture activity using smartphones, as well as in exploring the area of feedback in motion gesture interaction.

  • 23. Eliasson, P.
    et al.
    Gong, Jing
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Nordström, J.
    A stable and conservative coupling of the unsteady compressible navier-stokes equations at interfaces using finite difference and finite volume methods2018In: AIAA Aerospace Sciences Meeting, 2018, American Institute of Aeronautics and Astronautics Inc, AIAA , 2018, no 210059Conference paper (Refereed)
    Abstract [en]

    Stable and conservative interface boundary conditions are developed for the unsteady compressible Navier-Stokes equations using finite difference and finite volume methods. The finite difference approach is based on summation-by-part operators and can be made higher order accurate with boundary conditions imposed weakly. The finite volume approach is an edge- and dual grid-based approach for unstructured grids, formally second order accurate in space, with weak boundary conditions as well. Stable and conservative weak boundary conditions are derived for interfaces between finite difference methods, for finite volume methods and for the coupling between the two approaches. The three types of interface boundary conditions are demonstrated for two test cases. Firstly, inviscid vortex propagation with a known analytical solution is considered. The results show expected error decays as the grid is refined for various couplings and spatial accuracy of the finite difference scheme. The second test case involves viscous laminar flow over a cylinder with vortex shedding. Calculations with various coupling and spatial accuracies of the finite difference solver show that the couplings work as expected and that the higher order finite difference schemes provide enhanced vortex propagation.

  • 24.
    Everitt, Niklas
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Galrinho, Miguel
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Open-loop asymptotically efficient model reduction with the Steiglitz–McBride method2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 89, p. 221-234Article in journal (Refereed)
    Abstract [en]

    In system identification, it is often difficult to use a physical intuition when choosing a noise model structure. The importance of this choice is that, for the prediction error method (PEM) to provide asymptotically efficient estimates, the model orders must be chosen according to the true system. However, if only the plant estimates are of interest and the experiment is performed in open loop, the noise model can be over-parameterized without affecting the asymptotic properties of the plant. The limitation is that, as PEM suffers in general from non-convexity, estimating an unnecessarily large number of parameters will increase the risk of getting trapped in local minima. Here, we consider the following alternative approach. First, estimate a high-order ARX model with least squares, providing non-parametric estimates of the plant and noise model. Second, reduce the high-order model to obtain a parametric model of the plant only. We review existing methods to do this, pointing out limitations and connections between them. Then, we propose a method that connects favorable properties from the previously reviewed approaches. We show that the proposed method provides asymptotically efficient estimates of the plant with open-loop data. Finally, we perform a simulation study suggesting that the proposed method is competitive with state-of-the-art methods.

  • 25.
    Ferizbegovic, Mina
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Galrinho, Miguel
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Weighted Null-Space Fitting for Cascade Networks with Arbitrary Location of Sensors and Excitation Signals2018In: : 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 4707-4712Conference paper (Refereed)
    Abstract [en]

    Identification of a complete dynamic network affected by sensor noise using the prediction error method is often too complex. One of the reasons for this complexity is the requirement to minimize a non-convex cost function, which becomes more difficult with more complex networks. In this paper, we consider serial cascade networks affected by sensor noise. Recently, the Weighted Null-Space Fitting method has been shown to be appropriate for this setting, providing asymptotically efficient estimates without suffering from non-convexity; however, applicability of the method was subject to some conditions on the locations of sensors and excitation signals. In this paper, we drop such conditions, proposing an extension of the method that is applicable to general serial cascade networks. We formulate an algorithm that describes application of the method in a general setting, and perform a simulation study to illustrate the performance of the method, which suggests that this extension is still asymptotically efficient.

  • 26.
    Feyzmahdavian, Hamid Reza
    et al.
    ABB Corp Res Ctr, S-72226 Vasteras, Sweden..
    Besselink, Bart
    Univ Groningen, Johann Bernoulli Inst Math & Comp Sci, NL-9712 CP Groningen, Netherlands..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Stability Analysis of Monotone Systems via Max-Separable Lyapunov Functions2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 3, p. 643-656Article in journal (Refereed)
    Abstract [en]

    We analyze stability properties of monotone nonlinear systems via max-separable Lyapunov functions, motivated by the following observations: first, recent results have shown that asymptotic stability of a monotone nonlinear system implies the existence of a max-separable Lyapunov function on a compact set; second, for monotone linear systems, asymptotic stability implies the stronger properties of D-stability and insensitivity to time delays. This paper establishes that for monotone nonlinear systems, equivalence holds between asymptotic stability, the existence of a max-separable Lyapunov function, D-stability, and insensitivity to bounded and unbounded time-varying delays. In particular, a new and general notion of D-stability for monotone nonlinear systems is discussed, and a set of necessary and sufficient conditions for delay-independent stability are derived. Examples show how the results extend the state of the art.

  • 27.
    Galrinho, Miguel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Parametric Identification Using Weighted Null-Space Fitting2019In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 64, no 7, p. 2798-2813Article in journal (Refereed)
    Abstract [en]

    In identification of dynamical systems, the prediction error method with a quadratic cost function provides asymptotically efficient estimates under Gaussian noise, but in general it requires solving a nonconvex optimization problem, which may imply convergence to nonglobal minima. An alternative class of methods uses a nonparametric model as intermediate step to obtain the model of interest. Weighted null-space fitting (WNSF) belongs to this class, starting with the estimate of a nonparametric ARX model with least squares. Then, the reduction to a parametric model is a multistep procedure where each step consists of the solution of a quadratic optimization problem, which can be obtained with weighted least squares. The method is suitable for both open- and closed-loop data, and can be applied to many common parametric model structures, including output-error, ARMAX, and Box-Jenkins. The price to pay is the increase of dimensionality in the nonparametric model, which needs to tend to infinity as function of the sample size for certain asymptotic statistical properties to hold. In this paper, we conduct a rigorous analysis of these properties: namely, consistency, and asymptotic efficiency. Also, we perform a simulation study illustrating the performance of WNSF and identify scenarios where it can be particularly advantageous compared with state-of-the-art methods.

  • 28.
    Gao, Yulong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Wu, Shuang
    Hong Kong Univ Sci & Technol, Elect & Comp Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Shi, Ling
    Hong Kong Univ Sci & Technol, Elect & Comp Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China..
    Xie, Lihua
    Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore..
    Stochastic Optimal Control of Dynamic Queue Systems: A Probabilistic Perspective2018In: 2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), IEEE , 2018, p. 837-842Conference paper (Refereed)
    Abstract [en]

    Queue overflow of a dynamic queue system gives rise to the information loss (or packet loss) in the communication buffer or the decrease of throughput in the transportation network. This paper investigates a stochastic optimal control problem for dynamic queue systems when imposing probability constraints on queue overflows. We reformulate this problem as a Markov decision process (MDP) with safety constraints. We prove that both finite-horizon and infinite-horizon stochastic optimal control for MDP with such constraints can be transformed as a linear program (LP), respectively. Feasibility conditions are provided for the finite-horizon constrained control problem. Two implementation algorithms are designed under the assumption that only the state (not the state distribution) can be observed at each time instant. Simulation results compare optimal cost and state distribution among different scenarios, and show the probability constraint satisfaction by the proposed algorithms.

  • 29.
    George, Jemin
    et al.
    US Army Res Lab, Adelphi, MD 20783 USA..
    Yi, Xinlei
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Yang, Tao
    Univ North Texas, Dept Elect Engn, Denton, TX 76203 USA..
    Distributed Robust Dynamic Average Consensus with Dynamic Event-Triggered Communication2018In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 434-439Conference paper (Refereed)
    Abstract [en]

    This paper presents the formulation and analysis of a fully distributed dynamic event-triggered communication based robust dynamic average consensus algorithm. Dynamic average consensus problem involves a networked set of agents estimating the time-varying average of dynamic reference signals locally available to individual agents. We propose an asymptotically stable solution to the dynamic average consensus problem that is robust to network disruptions. Since this robust algorithm requires continuous communication among agents, we introduce a novel dynamic event-triggered communication scheme to reduce the overall inter-agent communications. It is shown that the event-triggered algorithm is asymptotically stable and free of Zeno behavior. Numerical simulations are provided to illustrate the effectiveness of the proposed algorithm.

  • 30.
    Gonzalez, Rodrigo A.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Welsh, James S.
    Univ Newcastle, Sch Elect Engn & Comp Sci, Callaghan, NSW, Australia..
    An asymptotically optimal indirect approach to continuous-time system identification2018In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 638-643Conference paper (Refereed)
    Abstract [en]

    The indirect approach to continuous-time system identification consists in estimating continuous-time models by first determining an appropriate discrete-time model. For a zero-order hold sampling mechanism, this approach usually leads to a transfer function estimate with relative degree 1, independent of the relative degree of the strictly proper real system. In this paper, a refinement of these methods is developed. Inspired by the indirect prediction error method, we propose an estimator that enforces a fixed relative degree in the continuous-time transfer function estimate, and show that the estimator is consistent and asymptotically efficient. Extensive numerical simulations are put forward to show the performance of this estimator when contrasted with other indirect and direct methods for continuous-time system identification.

  • 31. Guo, Meng
    et al.
    Bechlioulis, Charalampos P.
    Kyriakopoulos, Kostas J.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Hybrid Control of Multiagent Systems With Contingent Temporal Tasks and Prescribed Formation Constraints2017In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 4, no 4, p. 781-792Article in journal (Refereed)
    Abstract [en]

    In this paper, we present a distributed hybrid control strategy for multiagent systems with contingent temporal tasks and prescribed formation constraints. Each agent is assigned a local task given as a linear temporal logic formula. In addition, two commonly seen kinds of cooperative robotic tasks, namely, service and formation, are requested and exchanged among the agents in real time. The service request is a short-term task provided by one agent to another. On the other hand, the formation request is a relative deployment requirement with predefined transient response imposed by an associated performance function. The proposed hybrid control strategy consists of four major components: 1) the contingent requests handlingmodule; 2) the real-time events monitoring module; 3) the local discrete plan synthesis module; and 4) the continuous control switching module, and it is shown that all local tasks and contingent service/formation requests are fulfilled. Finally, a simulated paradigm demonstrates the proposed control strategy.

  • 32.
    Guo, Meng
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Boskos, Dimitris
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Distributed hybrid control synthesis for multi-agent systems from high-level specifications2018In: Control Subject to Computational and Communication Constraints, Springer Verlag , 2018, 475, p. 241-260Chapter in book (Refereed)
    Abstract [en]

    Current control applications necessitate in many cases the consideration of systems with multiple interconnected components. These components/agents may need to fulfill high-level tasks at a discrete planning layer and also coupled constraints at the continuous control layer. Toward this end, the need for combined decentralized control at the continuous layer and planning at the discrete layer becomes apparent. While there are approaches that handle the problem in a top-down centralized manner, decentralized bottom-up approaches have not been pursued to the same extent. We present here some of our results for the problem of combined, hybrid control and task planning from high-level specifications for multi-agent systems in a bottom-up manner. In the first part, we present some initial results on extending the necessary notion of abstractions to multi-agent systems in a distributed fashion. We then consider a setup where agents are assigned individual tasks in the form of linear temporal logic (LTL) formulas and derive local task planning strategies for each agent. In the last part, the problem of combined distributed task planning and control under coupled continuous constraints is further considered.

  • 33.
    Guo, Ziyang
    et al.
    Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China. hi, Dawei.
    Shi, Dawei
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Shi, Ling
    Worst-Case Innovation-Based Integrity Attacks With Side Information on mote State Estimation2019In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 6, no 1, p. 48-59Article in journal (Refereed)
    Abstract [en]

    In this paper, we study the worst-case consequence of innovation-based tegrity attacks with side information in a remote state estimation enario where a sensor transmits its measurement to a remote estimator uipped with a false-data detector. If a malicious attacker is not only le to compromise the transmitted data packet but also able to measure e system state itself, the attack strategy can be designed based on e intercepted data, the sensing data, or alternatively the combined formation. Surprisingly, we show that launching attacks using the mbined information are not always optimal. First, we characterize the ealthiness constraints for different types of attack strategies to oid being noticed by the false-data detector. Then, we derive the olution of the remote estimation error covariance in the presence of tacks, based on which the worst-case attack policies are obtained by lving convex optimization problems. Furthermore, the closed-form pressions of the worst-case attacks are obtained for scalar systems d the attack consequences are compared with the existing work to termine which strategy is more critical in deteriorating system rformance. Simulation examples are provided to illustrate the alytical results.

  • 34.
    Ha, Huong
    et al.
    Univ Newcastle, Sch Elect Engn & Comp, Newcastle, NSW, Australia..
    Welsh, James S.
    Univ Newcastle, Sch Elect Engn & Comp, Newcastle, NSW, Australia..
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Wahlberg, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    An analysis of the SPARSEVA estimate for the finite sample data case2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 96, p. 141-149Article in journal (Refereed)
    Abstract [en]

    In this paper, we develop an upper bound for the SPARSEVA (SPARSe Estimation based on a VAlidation criterion) estimation error in a general scheme, i.e., when the cost function is strongly convex and the regularized norm is decomposable for a pair of subspaces. We show how this general bound can be applied to a sparse regression problem to obtain an upper bound of the estimation error for the traditional I-1 SPARSEVA problem. Numerical results are used to illustrate the effectiveness of the suggested bound. 

  • 35.
    Hashimoto, Kazumune
    et al.
    Keio Univ, Dept Appl Phys & Physicoinformat, Yokohama, Kanagawa, Japan..
    Adachi, Shuichi
    Keio Univ, Dept Appl Phys & Physicoinformat, Yokohama, Kanagawa, Japan..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Energy-aware networked control systems under temporal logic specifications2018In: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 132-139Conference paper (Refereed)
    Abstract [en]

    In recent years, event and self-triggered control have been proposed as energy-aware control strategies to expand the life-time of battery powered devices in Networked Control Systems (NCSs). In contrast to the previous works in which their control objective is to achieve stability, this paper presents a novel energy-aware control scheme for achieving high level specifications, or more specifically, temporal logic specifications. Inspired by the standard hierarchical strategy that has been proposed in the field of formal control synthesis paradigm, we propose a new abstraction procedure for jointly synthesizing control and communication strategies, such that the communication reduction in NCSs and the satisfaction of the temporal logic specifications are guaranteed. The benefits of the proposal are illustrated through a numerical example.

  • 36.
    Heshmati-Alamdari, Shahab
    et al.
    Natl Tech Univ Athens, Dept Mech Engn, Control Syst Lab, 9 Heroon Polytech St, Zografos 15780, Greece..
    Bechlioulis, Charalampos P.
    Natl Tech Univ Athens, Dept Mech Engn, Control Syst Lab, 9 Heroon Polytech St, Zografos 15780, Greece..
    Karras, George C.
    Natl Tech Univ Athens, Dept Mech Engn, Control Syst Lab, 9 Heroon Polytech St, Zografos 15780, Greece..
    Nikou, Alexandros
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH Royal Inst Technol, KTH Ctr Autonomous Syst, SE-10044 Stockholm, Sweden..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH Royal Inst Technol, KTH Ctr Autonomous Syst, SE-10044 Stockholm, Sweden..
    Kyriakopoulos, Kostas J.
    Natl Tech Univ Athens, Dept Mech Engn, Control Syst Lab, 9 Heroon Polytech St, Zografos 15780, Greece..
    A robust interaction control approach for underwater vehicle manipulator systems2018In: Annual Reviews in Control, ISSN 1367-5788, E-ISSN 1872-9088, Vol. 46, p. 315-325Article, review/survey (Refereed)
    Abstract [en]

    In underwater robotic interaction tasks (e.g., sampling of sea organisms, underwater welding, panel handling, etc) various issues regarding the uncertainties and complexity of the robot dynamic model, the external disturbances (e.g., sea currents), the steady state performance as well as the overshooting/undershooting of the interaction force error, should be addressed during the control design. Motivated by the aforementioned considerations, this paper presents a force/position tracking control protocol for an Underwater Vehicle Manipulator System (UVMS) in compliant contact with a planar surface, without incorporating any knowledge of the UVMS dynamic model, the exogenous disturbances or the contact stiffness model. Moreover, the proposed control framework guarantees: (i) certain predefined minimum speed of response, maximum steady state error as well as overshoot/undershoot concerning the force/position tracking errors, (ii) contact maintenance and (iii) bounded closed loop signals. Additionally, the achieved transient and steady state performance is solely determined by certain designer-specified performance functions/parameters and is fully decoupled from the control gain selection and the initial conditions. Finally, both simulation and experimental studies clarify the proposed method and verify its efficiency.

  • 37.
    Jansson, Niclas
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Improving Strong Scalability Limits of Finite Element Based Solvers2019Conference paper (Refereed)
    Abstract [en]

    Current finite element codes scale reasonably well as long as each core has sufficient amount of local work that can balance communication costs. However, achieving efficient performance at exascale will require unreasonable large problem sizes, in particular for low-order methods, where the small amount of work per element already is a limiting factor on current post petascale machines. One of the key bottlenecks for these methods is sparse matrix assembly, where communication latency starts to limit performance as the number of cores increases. We present our work on improving strong scalability limits of message passing based general low-order finite element based solvers. Using lightweight one-sided communication, we demonstrate that the scalability of performance critical, latency sensitive kernels can achieve almost an order of magnitude better scalability. We introduce a new hybrid MPI/PGAS implementation of the open source general finite element framework FEniCS, replacing the linear algebra backend with a new library written in UPC. A detailed description of the implementation and the hybrid interface to FEniCS is given, and we present a detailed performance study of the hybrid implementation on Cray XC40 machines.

  • 38.
    Javid, Alireza M.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Mutual Information Preserving Analysis of a Single Layer Feedforward Network2018In: Proceedings of the International Symposium on Wireless Communication Systems, VDE Verlag GmbH , 2018Conference paper (Refereed)
    Abstract [en]

    We construct a single layer feed forward network and analyze the constructed system using information theoretic tools, such as mutual information and data processing inequality. We derive a threshold on the number of hidden nodes required to achieve a good classification performance. Classification performance is expected to saturate as we increase the number of hidden nodes more than the threshold. The threshold is further verified by experimental studies on benchmark datasets. Index Terms-Neural networks, mutual information, extreme learning machine, invertible function.

  • 39.
    Khirirat, Sarit
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Alistarh, Dan
    IST Austria, Vienna, Austria..
    Gradient compression for communication-limited convex optimization2018In: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 166-171, article id 8619625Conference paper (Refereed)
    Abstract [en]

    Data-rich applications in machine-learning and control have motivated an intense research on large-scale optimization. Novel algorithms have been proposed and shown to have optimal convergence rates in terms of iteration counts. However, their practical performance is severely degraded by the cost of exchanging high-dimensional gradient vectors between computing nodes. Several gradient compression heuristics have recently been proposed to reduce communications, but few theoretical results exist that quantify how they impact algorithm convergence. This paper establishes and strengthens the convergence guarantees for gradient descent under a family of gradient compression techniques. For convex optimization problems, we derive admissible step sizes and quantify both the number of iterations and the number of bits that need to be exchanged to reach a target accuracy. Finally, we validate the performance of different gradient compression techniques in simulations. The numerical results highlight the properties of different gradient compression algorithms and confirm that fast convergence with limited information exchange is possible.

  • 40.
    Kim, Jeemin
    et al.
    Yonsei Univ, Sch Elect & Elect Engn, Seoul 03722, South Korea..
    Park, Jihong
    Univ Oulu, Ctr Wireless Commun, Oulu 90014, Finland..
    Kim, Seunghwan
    Yonsei Univ, Sch Elect & Elect Engn, Seoul 03722, South Korea..
    Kim, Seong-Lyun
    Yonsei Univ, Sch Elect & Elect Engn, Seoul 03722, South Korea..
    Sung, Ki Won
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Center for Wireless Systems, Wireless@kth.
    Kim, Kwang Soon
    Yonsei Univ, Sch Elect & Elect Engn, Seoul 03722, South Korea..
    Millimeter-Wave Interference Avoidance via Building-Aware Associations2018In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 10618-10634Article in journal (Refereed)
    Abstract [en]

    Signal occlusion by building blockages is a double-edged sword for the performance of millimeter-wave (mmW) communication networks. Buildings may dominantly attenuate the useful signals, especially when mmW base stations (BSs) are sparsely deployed compared with the building density. In the opposite BS deployment, buildings can block the undesired interference. To enjoy only the benefit, we propose a building-aware association scheme that adjusts the directional BS association bias of the user equipments (UEs), based on a given building density and the concentration of UE locations around the buildings. The association of each BS can thereby be biased: 1) toward the UEs located against buildings for avoiding interference to other UEs or 2) toward the UEs providing their maximum reference signal received powers. The proposed association scheme is optimized to maximize the downlink average data rate derived by stochastic geometry. Its effectiveness is validated by simulation using real building statistics.

  • 41.
    Kokic, Mia
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Antonova, Rika
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Stork, Johannes A.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Kragic, Danica
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation2018In: Proceedings of The 2nd Conference on Robot Learning, PMLR 87, 2018, p. 641-650Conference paper (Refereed)
    Abstract [en]

    We develop an approach that benefits from large simulated datasets and takes full advantage of the limited online data that is most relevant. We propose a variant of Bayesian optimization that alternates between using informed and uninformed kernels. With this Bernoulli Alternation Kernel we ensure that discrepancies between simulation and reality do not hinder adapting robot control policies online. The proposed approach is applied to a challenging real-world problem of task-oriented grasping with novel objects. Our further contribution is a neural network architecture and training pipeline that use experience from grasping objects in simulation to learn grasp stability scores. We learn task scores from a labeled dataset with a convolutional network, which is used to construct an informed kernel for our variant of Bayesian optimization. Experiments on an ABB Yumi robot with real sensor data demonstrate success of our approach, despite the challenge of fulfilling task requirements and high uncertainty over physical properties of objects.

  • 42.
    Kouyoumdjieva, Sylvia T.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Karlsson, Gunnar
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Experimental Evaluation of Precision of a Proximity-based Indoor Positioning System2019Conference paper (Refereed)
    Abstract [en]

    Bluetooth Low Energy beacons are small transmitters with long battery life that are considered for providing proximity-based services. In this work we evaluate experimentally the performance of a proximity-based indoor positioning system built with off-the-shelf beacons in a realistic environment. We demonstrate that the performance of the system depends on a number of factors, such as the distance between the beacon and the mobile device, the positioning of the beacon as well as the presence and positioning of obstacles such as human bodies. We further propose an online algorithm based on moving average forecasting and evaluate the algorithm in the presence of human mobility. We conclude that algorithms for proximity-based indoor positioning must be evaluated in realistic scenarios, for instance considering people and traffic on the used radio bands. The uncertainty in positioning is high in our experiments and hence the success of commercial context-aware solutions based on BLE beacons is highly dependent on the accuracy required by each application.

  • 43.
    Kutzner, Carsten
    et al.
    Max Planck Inst Biophys Chem, Theoret & Computat Biophys, Fassberg 11, D-37077 Gottingen, Germany. al$$$l, Szilard.
    Páll, Szilard
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Fechner, Martin
    Esztermann, Ansgar
    de Groot, Bert L.
    Grubmüller, Helmut
    More bang for your buck: Improved use of GPU nodes for GROMACS 20182019In: Journal of Computational Chemistry, ISSN 0192-8651, E-ISSN 1096-987XArticle in journal (Refereed)
    Abstract [en]

    We identify hardware that is optimal to produce molecular dynamics (MD) trajectories on Linux compute clusters with the GROMACS 2018 simulation package. Therefore, we benchmark the GROMACS performance on a diverse set of compute nodes and relate it to the costs of the nodes, which may include their lifetime costs for energy and cooling. In agreement with our earlier investigation using GROMACS 4.6 on hardware of 2014, the performance to price ratio of consumer GPU nodes is considerably higher than that of CPU nodes. However, with GROMACS 2018, the optimal CPU to GPU processing power balance has shifted even more toward the GPU. Hence, nodes optimized for GROMACS 2018 and later versions enable a significantly higher performance to price ratio than nodes optimized for older GROMACS versions. Moreover, the shift toward GPU processing allows to cheaply upgrade old nodes with recent GPUs, yielding essentially the same performance as comparable brand-new hardware.

  • 44.
    Larsson, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Golden Angle Modulation2018In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, no 1, p. 98-101Article in journal (Refereed)
    Abstract [en]

    Quadrature amplitude modulation (QAM), with its uniform distribution, exhibits an asymptotic shaping-loss of pi e/6 (approximate to 1.53 dB) with increasing signal-to-noise-ratio compared to the additive white Gaussian noise Shannon capacity. With inspiration gained from special (leaf, flower petal, and seed) packing arrangements (spiral phyllotaxis) found among plants, a novel, shape-versatile, circular symmetric, modulation scheme, the golden angle modulation (GAM) is introduced. Disc-shaped, and complex Gaussian approximating bell-shaped, GAM-signal constellations are considered. For bell-GAM, a high-rate approximation, and a mutual information optimization formulation, are developed. Bell-GAM overcomes the asymptotic shaping-loss seen in QAM, and offers Shannon capacity approaching performance. Transmitter resource limited links, such as space probe-to-earth, and mobile-to-basestation, are cases where GAM could be particularly valuable.

  • 45. Larsson, Torbjörn
    et al.
    Hammar, Johan
    Gong, Jing
    KTH, Centres, SeRC - Swedish e-Science Research Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Barth, Michaela
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Axner, Lilit
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    ENHANCING COMPUTATIONAL AERO-ACOUSTIC PROCESSES FOR GROUNDVEHICLES RESOLVING OPEN SOURCE CFD2018In: The 13th OpenFOAM Workshop, 2018, p. 1-4Conference paper (Refereed)
  • 46.
    Laure, Erwin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Ahlin, Daniel
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Malinowsky, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Svensson, Gert
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Vincent, Jonathan
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Lindgren the Swedish tier-1 system2015In: Contemporary High Performance Computing: From Petascale Toward Exascale: Volume Two, CRC Press , 2015, p. 141-162Chapter in book (Other academic)
    Abstract [en]

    The Swedish academic computing landscape is organized under the auspices of SNIC, the Swedish National Infrastructure for Computing. SNIC coordinates investments in computing and storage infrastructure at its six national centers and manages the national process for allocating research time on its computing resources. Since its formation in 2003, SNIC has significantly increased the computational capacity available to Swedish researchers and firmly put Sweden on the international computational science map. When the Partnership for Advanced Computing in Europe (PRACE) started in 2010, SNIC joined this European HPC effort and worked with the Swedish Research 142Council to allocate additional funds for a national high-end system that would also be made available to European researchers via PRACE. These efforts resulted in the installation of a CRAY XE6 supercomputer, named Lindgren, at the PDC Center for High-Performance Computing at the KTH Royal Institute of Technology in Stockholm. 

  • 47.
    Li, Nan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Rasmussen, Lars Kildehöj
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Optimized Cooperative Multiple Access in Industrial Cognitive Networks2018In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 14, no 6, p. 2666-2676Article in journal (Refereed)
    Abstract [en]

    We consider optimized cooperation in joint orthogonal multiple access and nonorthogonal multiple access in industrial cognitive networks, in which lots of devices may have to share spectrum and some devices (e.g., those for critical control devices) have higher transmission priority, known as primary users. We consider one secondary transmitter (less important devices) as a potential relay between a primary transmitter and receiver pair. The choice of cooperation scheme differs in terms of use cases. With decode-and-forward relaying, the channel between the primary and secondary users limits the achievable rates especially when it experiences poor channel conditions. To alleviate this problem, we apply analog network coding to directly combine the received primary message for relaying with the secondary message. We find achievable rate regions for these two schemes over Rayleigh fading channels. We then investigate an optimization problem jointly considering orthogonalmultiple access and nonorthogonal multiple access, where the secondary rate is maximized under the constraint of maintaining the primary rate. We find both analytical solutions as well as solutions based on experiments through the time sharing strategy between the primary and secondary system and the transmit power allocation strategy at the secondary transmitter. We show the performance improvements of exploiting analog network coding and the impacts of cooperative schemes and user geometry on achievable rates and resource sharing strategies.

  • 48.
    Li, Nan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rasmussen, Lars Kildehöj
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Spectrum Sharing With Network Coding for Multiple Cognitive Users2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 1, p. 230-238Article in journal (Refereed)
    Abstract [en]

    In this paper, an intelligently cooperative communication network with cognitive users is considered, where in a primary system and a secondary system, respectively, a message is communicated to their respective receiver over a packet-based wireless link. The secondary system assists in the transmission of the primary message employing network coding, on the condition of maintaining or improving the primary performance, and is granted limited access to the transmission resources as a reward. The users in both systems exploit their previously received information in encoding and decoding the binary combined packets. Considering the priority of legitimate users, a selective cooperation mechanism is investigated and the system performance based on an optimization problem is analyzed. Both the analytical and numerical results show that the condition for the secondary system accessing the licensed spectrum resource is when the relay link performs better than the direct link of the primary transmission. We also extend the system model into a network with multiple secondary users and propose two relay selection algorithms. Jointly considering the related link qualities, a best relay selection and a best relay group selection algorithm are discussed. Overall, it is found that the throughput performance can be improved with multiple secondary users, especially with more potential users cooperating in the best relay group selection algorithm.

  • 49.
    Li, Qizhao
    et al.
    East China Univ Sci & Technol, Key Lab Adv Mat, Feringa Nobel Prize Scientist Joint Res Ctr, Sch Chem & Mol Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China.;East China Univ Sci & Technol, Joint Int Res Lab Precis Chem & Mol Engn, Feringa Nobel Prize Scientist Joint Res Ctr, Sch Chem & Mol Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China..
    Ishida, Masatoshi
    Kyushu Univ, Dept Chem & Biochem, Grad Sch Engn, Fukuoka 8190395, Japan.;Kyushu Univ, Ctr Mol Syst, Fukuoka 8190395, Japan..
    Kai, Hiroto
    Kyushu Univ, Dept Chem & Biochem, Grad Sch Engn, Fukuoka 8190395, Japan.;Kyushu Univ, Ctr Mol Syst, Fukuoka 8190395, Japan..
    Gu, Tingting
    Jiangsu Univ, Sch Chem & Chem Engn, Zhenjiang 212013, Jiangsu, Peoples R China..
    Li, Chengjie
    East China Univ Sci & Technol, Key Lab Adv Mat, Feringa Nobel Prize Scientist Joint Res Ctr, Sch Chem & Mol Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China.;East China Univ Sci & Technol, Joint Int Res Lab Precis Chem & Mol Engn, Feringa Nobel Prize Scientist Joint Res Ctr, Sch Chem & Mol Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China..
    Li, Xin
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    Baryshnikov, Glib
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    Liang, Xu
    Jiangsu Univ, Sch Chem & Chem Engn, Zhenjiang 212013, Jiangsu, Peoples R China..
    Zhu, Weihua
    Jiangsu Univ, Sch Chem & Chem Engn, Zhenjiang 212013, Jiangsu, Peoples R China..
    Ågren, Hans
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology. KTH Royal Inst Technol, Dept Theoret Chem & Biol, Sch Biotechnol, S-10691 Stockholm, Sweden..
    Furuta, Hiroyuki
    Kyushu Univ, Dept Chem & Biochem, Grad Sch Engn, Fukuoka 8190395, Japan.;Kyushu Univ, Ctr Mol Syst, Fukuoka 8190395, Japan..
    Xie, Yongshu
    East China Univ Sci & Technol, Key Lab Adv Mat, Feringa Nobel Prize Scientist Joint Res Ctr, Sch Chem & Mol Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China.;East China Univ Sci & Technol, Joint Int Res Lab Precis Chem & Mol Engn, Feringa Nobel Prize Scientist Joint Res Ctr, Sch Chem & Mol Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China..
    Skeletal Rearrangement of Twisted Thia-Norhexaphyrin: Multiply Annulated Polypyrrolic Aromatic Macrocycles2019In: Angewandte Chemie International Edition, ISSN 1433-7851, E-ISSN 1521-3773, Vol. 58, no 18, p. 5925-5929Article in journal (Refereed)
    Abstract [en]

    A hybrid thia-norhexaphyrin comprising a directly linked N-confused pyrrole and thiophene unit (1) revealed unique macrocycle transformations to afford multiply inner-annulated aromatic macrocycles. Oxidation with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone triggered a cleavage of the C-S bond of the thiophene unit, accompanied with skeletal rearrangement to afford unique pi-conjugated products: a thiopyrrolo-pentaphyrin embedded with a pyrrolo[1,2]isothiazole (2), a sulfur-free pentaphyrin incorporating an indolizine moiety (3), and a thiopyranyltriphyrinoid containing a 2H-thiopyran unit (4). Furthermore, 2 underwent desulfurization reactions to afford a fused pentaphyrin containing a pyrrolizine moiety (5) under mild conditions. Using expanded porphyrin scaffolds, oxidative thiophene cleavage and desulfurization of the hitherto unknown N-confused core-modified macrocycles would be a practical approach for developing unique polypyrrolic aromatic macrocycles.

  • 50.
    Liang, Xinyue
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Javid, Alireza M.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    DISTRIBUTED LARGE NEURAL NETWORK WITH CENTRALIZED EQUIVALENCE2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 2976-2980Conference paper (Refereed)
    Abstract [en]

    In this article, we develop a distributed algorithm for learning a large neural network that is deep and wide. We consider a scenario where the training dataset is not available in a single processing node, but distributed among several nodes. We show that a recently proposed large neural network architecture called progressive learning network (PLN) can be trained in a distributed setup with centralized equivalence. That means we would get the same result if the data be available in a single node. Using a distributed convex optimization method called alternating-direction-method-of-multipliers (ADMM), we perform training of PLN in the distributed setup.

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