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Publications (10 of 573) Show all publications
Stankovic, M. S., Stankovic, S. S. & Johansson, K. H. (2018). Asynchronous Distributed Blind Calibration of Sensor Networks Under Noisy Measurements. IEEE Transactions on Big Data, 5(1), 571-582
Open this publication in new window or tab >>Asynchronous Distributed Blind Calibration of Sensor Networks Under Noisy Measurements
2018 (English)In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 1, p. 571-582Article in journal (Refereed) Published
Abstract [en]

In this paper, a novel distributed algorithm for asynchronous blind macro-calibration in sensor networks with noisy measurements is proposed. The algorithm is formulated as a set of instrumental variable type recursions for estimating parameters of sensor calibration functions. It is proved using asynchronous stochastic approximation arguments and properties of block-diagonally dominant matrices that the algorithm achieves asymptotic consensus for sensor gains and offsets in the mean square sense and with probability one. Recommendations for system design in terms of the choice of a priori tunable weights are provided. Special attention is paid to the situation when a subset of sensors in the network (reference sensors) remains with fixed characteristics. In the case of only one reference sensor, convergence of the remaining sensors to its characteristics is proved. In the case of more than one reference sensor, it is proved that the calibration parameters converge to points that depend only on the characteristics of the reference sensors and the network properties.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-225732 (URN)10.1109/TCNS.2016.2633788 (DOI)000427871900050 ()2-s2.0-85044502030 (Scopus ID)
Funder
Swedish Research CouncilKnut and Alice Wallenberg Foundation
Note

QC 20180410

Available from: 2018-04-10 Created: 2018-04-10 Last updated: 2018-04-10Bibliographically approved
Stanković, M. S., Stanković, S. S. & Johansson, K. H. (2018). Distributed time synchronization for networks with random delays and measurement noise. Automatica, 93, 126-137
Open this publication in new window or tab >>Distributed time synchronization for networks with random delays and measurement noise
2018 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 93, p. 126-137Article in journal (Refereed) Published
Abstract [en]

In this paper a new distributed asynchronous algorithm is proposed for time synchronization in networks with random communication delays, measurement noise and communication dropouts. Three different types of the drift correction algorithm are introduced, based on different kinds of local time increments. Under nonrestrictive conditions concerning network properties, it is proved that all the algorithm types provide convergence in the mean square sense and with probability one (w.p.1) of the corrected drifts of all the nodes to the same value (consensus). An estimate of the convergence rate of these algorithms is derived. For offset correction, a new algorithm is proposed containing a compensation parameter coping with the influence of random delays and special terms taking care of the influence of both linearly increasing time and drift correction. It is proved that the corrected offsets of all the nodes converge in the mean square sense and w.p.1. An efficient offset correction algorithm based on consensus on local compensation parameters is also proposed. It is shown that the overall time synchronization algorithm can also be implemented as a flooding algorithm with one reference node. It is proved that it is possible to achieve bounded error between local corrected clocks in the mean square sense and w.p.1. Simulation results provide an additional practical insight into the algorithm properties and show its advantage over the existing methods.

Place, publisher, year, edition, pages
Elsevier, 2018
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-227532 (URN)10.1016/j.automatica.2018.03.054 (DOI)000436916200015 ()2-s2.0-85044584487 (Scopus ID)
Funder
EU, FP7, Seventh Framework Programme, PCIG12-GA-2012-334098Knut and Alice Wallenberg FoundationSwedish Foundation for Strategic Research Swedish Research Council
Note

QC 20180518

Available from: 2018-05-18 Created: 2018-05-18 Last updated: 2018-07-17Bibliographically approved
Parisio, A., Molinari, M., Varagnolo, D. & Johansson, K. H. (2018). Energy management systems for intelligent buildings in smart grids. In: Intelligent Building Control Systems: A Survey of Modern Building Control and Sensing Strategies (pp. 253-291). Springer (9783319684611)
Open this publication in new window or tab >>Energy management systems for intelligent buildings in smart grids
2018 (English)In: Intelligent Building Control Systems: A Survey of Modern Building Control and Sensing Strategies, Springer, 2018, no 9783319684611, p. 253-291Chapter in book (Refereed)
Abstract [en]

The next-generation electric grid needs to be smart and sustainable to simultaneously deal with the ever-growing global energy demand and achieve environmental goals. In this context, the role of residential and commercial buildings is crucial, due to their large share of primary energy usage worldwide. In this chapter, we describe energy management frameworks for buildings in a smart grid scenario. An Energy Management System (EMS) is responsible for optimally scheduling end-user smart appliances, heating systems, ventilation units, and local generation devices. We discuss the performance and the practical implementation of novel stochastic MPC schemes for HVAC systems, and illustrate how these schemes take into account several sources of uncertainties, e.g., occupancy and weather conditions. Furthermore, we show how to integrate local generation capabilities and storage systems into a holistic building energy management framework.

Place, publisher, year, edition, pages
Springer, 2018
Series
Advances in Industrial Control, ISSN 1430-9491
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-220413 (URN)10.1007/978-3-319-68462-8_10 (DOI)2-s2.0-85037610275 (Scopus ID)978-3-319-68461-1 (ISBN)
Note

QC 20171220

Available from: 2017-12-20 Created: 2017-12-20 Last updated: 2017-12-20Bibliographically approved
Wei, J., Zhang, S., Adaldo, A., Johan, T., Hu, X. & Johansson, K. H. (2018). Finite-time attitude synchronization with distributed discontinuous protocols. IEEE Transactions on Automatic Control
Open this publication in new window or tab >>Finite-time attitude synchronization with distributed discontinuous protocols
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2018 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523Article in journal (Refereed) Published
Abstract [en]

The finite-time attitude synchronization problem is considered in this paper, where the rotation of each rigid body is expressed using the axis-angle representation. Two discontinuous and distributed controllers using the vectorized signum function are proposed, which guarantee almost global and local convergence, respectively. Filippov solutions and non-smooth analysis techniques are adopted to handle the discontinuities. Sufficient conditions are provided to guarantee finite-time convergence and boundedness of the solutions. Simulation examples are provided to verify the performances of the control protocols designed in this paper.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-227718 (URN)10.1109/TAC.2018.2797179 (DOI)
Note

QC 20180523

Available from: 2018-05-11 Created: 2018-05-11 Last updated: 2018-05-23Bibliographically approved
Valerio, T., Flärdh, O., Mårtensson, J. & Johansson, K. H. (2018). Fuel-optimal look-ahead adaptive cruise control for heavy-duty vehicles. In: 2018 Annual American Control Conference (ACC): . Paper presented at 82018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton Milwauke City CenterMilwauke, United States, 27 June 2018 through 29 June 2018 (pp. 1841-1848). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8431494.
Open this publication in new window or tab >>Fuel-optimal look-ahead adaptive cruise control for heavy-duty vehicles
2018 (English)In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1841-1848, article id 8431494Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we investigate the problem of how to optimally control a heavy-duty vehicle following another one, commonly referred as ad-hoc or non-cooperative platooning. The problem is formulated as an optimal control problem that exploits road topography information and the knowledge of the preceding vehicle speed trajectory to compute the optimal engine torque and gear request for the vehicle under control. The optimal control problem is implemented by dynamic programming and is tested in a simulation study that compares the performance of multiple longitudinal control strategies. The proposed look-ahead adaptive cruise controller is able to achieve fuel saving up to 7% with respect to the use of a reference vehicle-following controller, by combining the benefits of adjusting the inter-vehicular distance according to the future slope with those of alternating phases of throttling and freewheeling (driving in neutral gear).

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
Proceedings of the American Control Conference, ISSN 2378-5861
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-234864 (URN)10.23919/ACC.2018.8431494 (DOI)2-s2.0-85052593065 (Scopus ID)9781538654286 (ISBN)
Conference
82018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton Milwauke City CenterMilwauke, United States, 27 June 2018 through 29 June 2018
Note

QC 20180912

Available from: 2018-09-12 Created: 2018-09-12 Last updated: 2018-09-12Bibliographically approved
Zhu, S., Chen, C., Xu, J., Guan, X., Xie, L. & Johansson, K. H. (2018). Mitigating Quantization Effects on Distributed Sensor Fusion: A Least Squares Approach. IEEE Transactions on Signal Processing, 66(13), 3459-3474
Open this publication in new window or tab >>Mitigating Quantization Effects on Distributed Sensor Fusion: A Least Squares Approach
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2018 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 13, p. 3459-3474Article in journal (Refereed) Published
Abstract [en]

In this paper, we consider the problem of sensor fusion over networks with asymmetric links, where the common goal is linear parameter estimation. For the scenario of bandwidth-constrained networks, existing literature shows that nonvanishing errors always occur, which depend on the quantization scheme. To tackle this challenging issue, we introduce the notion of virtual measurements and propose a distributed solution LS-DSFS, which is a combination of a quantized consensus algorithm and the least squares approach. We provide detailed analysis of the LS-DSFS on its performance in terms of unbiasedness and mean square property. Analytical results show that the LS-DSFS is effective in smearing out the quantization errors, and achieving the minimum mean square error (MSE) among the existing centralized and distributed algorithms. Moreover, we characterize its rate of convergence in the mean square sense and that of the mean sequence. More importantly, we find that the LS-DSFS outperforms the centralized approaches within a moderate number of iterations in terms of MSE, and will always consume less energy and achieve more balanced energy expenditure as the number of nodes in the network grows. Simulation results are presented to validate theoretical findings and highlight the improvements over existing algorithms.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Distributed sensor fusion, bandwidth-constrained network, asymmetric links, least squares approach
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-231695 (URN)10.1109/TSP.2018.2830304 (DOI)000435193800005 ()2-s2.0-85046374955 (Scopus ID)
Note

QC 20180824

Available from: 2018-08-24 Created: 2018-08-24 Last updated: 2018-08-24Bibliographically approved
Johansson, A., Wei, J., Sandberg, H., Johansson, K. H. & Chen, J. (2018). Optimization of the H∞-norm of Dynamic Flow Networks. In: 2018 Annual American Control Conference (ACC): . Paper presented at 2018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton Milwauke City Center, Milwauke, United States, 27 June 2018 through 29 June 2018 (pp. 1280-1285). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Optimization of the H∞-norm of Dynamic Flow Networks
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2018 (English)In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1280-1285Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we study the H∞-norm of linear systems over graphs, which is used to model distribution networks. In particular, we aim to minimize the H∞-norm subject to allocation of the weights on the edges. The optimization problem is formulated with LMI (Linear-Matrix-Inequality) constraints. For distribution networks with one port, i.e., SISO systems, we show that the H∞-norm coincides with the effective resistance between the nodes in the port. Moreover, we derive an upper bound of the H∞-norm, which is in terms of the algebraic connectivity of the graph on which the distribution network is defined.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
Proceedings of the American Control Conference, ISSN 0743-1619
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-234711 (URN)10.23919/ACC.2018.8431398 (DOI)2-s2.0-85052568554 (Scopus ID)9781538654286 (ISBN)
Conference
2018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton Milwauke City Center, Milwauke, United States, 27 June 2018 through 29 June 2018
Note

QC 20180910

Available from: 2018-09-10 Created: 2018-09-10 Last updated: 2018-09-10Bibliographically approved
Nekouei, E., Skoglund, M. & Johansson, K. H. (2018). Privacy of Information Sharing Schemes in a Cloud-based Multi-sensor Estimation Problem. In: 2018 Annual American Control Conference (ACC): . Paper presented at 2018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton ,Milwauke City Center Milwauke, United States, 27 June 2018 through 29 June 2018 (pp. 998-1002). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8431192.
Open this publication in new window or tab >>Privacy of Information Sharing Schemes in a Cloud-based Multi-sensor Estimation Problem
2018 (English)In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 998-1002, article id 8431192Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we consider a multi-sensor estimation problem wherein each sensor collects noisy information about its local process, which is only observed by that sensor, and a common process, which is simultaneously observed by all sensors. The objective is to assess the privacy level of (the local process of) each sensor while the common process is estimated using cloud computing technology. The privacy level of a sensor is defined as the conditional entropy of its local process given the shared information with the cloud. Two information sharing schemes are considered: a local scheme, and a global scheme. Under the local scheme, each sensor estimates the common process based on its measurement and transmits its estimate to a cloud. Under the global scheme, the cloud receives the sum of the sensors' measurements. It is shown that, in the local scheme, the privacy level of each sensor is always above a certain level which is characterized using Shannon's mutual information. It is also proved that this result becomes tight as the number of sensors increases. We also show that the global scheme is asymptotically private, i.e., the privacy loss of the global scheme decreases to zero at the rate of O(1/M) where M is the number of sensors.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
Proceedings of the American Control Conference, ISSN 0743-1619
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-234705 (URN)10.23919/ACC.2018.8431192 (DOI)2-s2.0-85052564006 (Scopus ID)9781538654286 (ISBN)
Conference
2018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton ,Milwauke City Center Milwauke, United States, 27 June 2018 through 29 June 2018
Note

QC 20180910

Available from: 2018-09-10 Created: 2018-09-10 Last updated: 2018-09-10Bibliographically approved
Ren, X., Johansson, K. H., Shi, D. & Shi, L. (2018). Quickest Change Detection in Adaptive Censoring Sensor Networks. IEEE Transactions on Big Data, 5(1), 239-250
Open this publication in new window or tab >>Quickest Change Detection in Adaptive Censoring Sensor Networks
2018 (English)In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 1, p. 239-250Article in journal (Refereed) Published
Abstract [en]

The problem of quickest change detection with communication rate constraints is studied. A network of wireless sensors with limited computation capability monitors the environment and sends observations to a fusion center via wireless channels. At an unknown time instant, the distributions of observations at all the sensor nodes change simultaneously. Due to limited energy, the sensors cannot transmit at all the time instants. The objective is to detect the change at the fusion center as quickly as possible, subject to constraints on false detection and average communication rate between the sensors and the fusion center. A minimax formulation is proposed. The cumulative sum (CuSum) algorithm is used at the fusion center and censoring strategies are used at the sensor nodes. The censoring strategies, which are adaptive to the CuSum statistic, are fed back by the fusion center. The sensors only send observations that fall into prescribed sets to the fusion center. This CuSum adaptive censoring (CuSum-AC) algorithm is proved to be an equalizer rule and to be globally asymptotically optimal for any positive communication rate constraint, as the average run length to false alarm goes to infinity. It is also shown, by numerical examples, that the CuSum-AC algorithm provides a suitable trade-off between the detection performance and the communication rate.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Adaptive, asymptotically optimal, censoring, CuSum, minimax, quickest change detection, wireless sensor networks
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-225729 (URN)10.1109/TCNS.2016.2598250 (DOI)000427871900022 ()2-s2.0-85044505077 (Scopus ID)
Funder
Knut and Alice Wallenberg FoundationSwedish Foundation for Strategic Research Swedish Research Council
Note

QC 20180410

Available from: 2018-04-10 Created: 2018-04-10 Last updated: 2018-04-10Bibliographically approved
Ishizaki, T., Sadamoto, T., Imura, J.-i., Sandberg, H. & Johansson, K. H. (2018). Retrofit control: Localization of controller design and implementation. Paper presented at 55th IEEE Conference on Decision and Control (CDC), DEC 12-14, 2016, Las Vegas, NV. Automatica, 95, 336-346
Open this publication in new window or tab >>Retrofit control: Localization of controller design and implementation
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2018 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 95, p. 336-346Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a retrofit control method for stable network systems. The proposed approach is a control method that, rather than an entire system model, requires a model of the subsystem of interest for controller design. To design the retrofit controller, we use a novel approach based on hierarchical state-space expansion that generates a higher-dimensional cascade realization of a given network system. The upstream dynamics of the cascade realization corresponds to an isolated model of the subsystem of interest, which is stabilized by a local controller. The downstream dynamics can be seen as a dynamical model representing the propagation of interference signals among subsystems, the stability of which is equivalent to that of the original system. This cascade structure enables a systematic analysis of both the stability and control performance of the resultant closed-loop system. The resultant retrofit controller is formed as a cascade interconnection of the local controller and an output rectifier that rectifies an output signal of the subsystem of interest so as to conform to an output signal of the isolated subsystem model while acquiring complementary signals neglected in the local controller design, such as interconnection signals from neighboring subsystems. Finally, the efficiency of the retrofit control method is demonstrated through numerical examples of power systems control and vehicle platoon control. 

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD, 2018
Keywords
Hierarchical state-space expansion, Decentralized control, Model reduction, Distributed design
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-234162 (URN)10.1016/j.automatica.2018.05.033 (DOI)000441853900036 ()2-s2.0-85048106987 (Scopus ID)
Conference
55th IEEE Conference on Decision and Control (CDC), DEC 12-14, 2016, Las Vegas, NV
Note

QC 20181019

Available from: 2018-10-19 Created: 2018-10-19 Last updated: 2018-10-19Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9940-5929

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