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Yi, Xinlei
Publications (8 of 8) Show all publications
Yang, T., Yi, X., Wu, J., Yuan, Y., Wu, D., Meng, Z., . . . Johansson, K. H. (2019). A survey of distributed optimization. Annual Reviews in Control, 47, 278-305
Open this publication in new window or tab >>A survey of distributed optimization
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2019 (English)In: Annual Reviews in Control, ISSN 1367-5788, E-ISSN 1872-9088, Vol. 47, p. 278-305Article, review/survey (Refereed) Published
Abstract [en]

In distributed optimization of multi-agent systems, agents cooperate to minimize a global function which is a sum of local objective functions. Motivated by applications including power systems, sensor networks, smart buildings, and smart manufacturing, various distributed optimization algorithms have been developed. In these algorithms, each agent performs local computation based on its own information and information received from its neighboring agents through the underlying communication network, so that the optimization problem can be solved in a distributed manner. This survey paper aims to offer a detailed overview of existing distributed optimization algorithms and their applications in power systems. More specifically, we first review discrete-time and continuous-time distributed optimization algorithms for undirected graphs. We then discuss how to extend these algorithms in various directions to handle more realistic scenarios. Finally, we focus on the application of distributed optimization in the optimal coordination of distributed energy resources. 

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD, 2019
Keywords
Distributed optimization, Coordination of distributed energy resources
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-255519 (URN)10.1016/j.arcontrol.2019.05.006 (DOI)000474680200022 ()2-s2.0-85065858312 (Scopus ID)
Note

QC 20191022

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved
Yi, X., Liu, K., Dimarogonas, D. V. & Johansson, K. H. (2019). Dynamic Event-Triggered and Self-Triggered Control for Multi-agent Systems. IEEE Transactions on Automatic Control, 64(8), 3300-3307
Open this publication in new window or tab >>Dynamic Event-Triggered and Self-Triggered Control for Multi-agent Systems
2019 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 64, no 8, p. 3300-3307Article in journal (Refereed) Published
Abstract [en]

We propose two novel dynamic event-triggered control laws to solve the average consensus problem for first-order continuous-time multiagent systems over undirected graphs. Compared with the most existing triggering laws, the proposed laws involve internal dynamic variables, which play an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Moreover, some existing triggering laws are special cases of ours. For the proposed self-triggered algorithm, continuous agent listening is avoided as each agent predicts its next triggering time and broadcasts it to its neighbors at the current triggering time. Thus, each agent only needs to sense and broadcast at its triggering times, and to listen to and receive incoming information from its neighbors at their triggering times. It is proved that the proposed triggering laws make the state of each agent converge exponentially to the average of the agents' initial states if and only if the underlying graph is connected. Numerical simulations are provided to illustrate the effectiveness of the theoretical results.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Consensus, dynamic event-triggered control, multiagent systems, self-triggered control
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-257567 (URN)10.1109/TAC.2018.2874703 (DOI)000478694300016 ()2-s2.0-85054510419 (Scopus ID)
Note

QC 20190923

Available from: 2019-09-23 Created: 2019-09-23 Last updated: 2019-09-23Bibliographically approved
Wei, J., Yi, X., Sandberg, H. & Johansson, K. H. (2019). Nonlinear Consensus Protocols With Applications to Quantized Communication and Actuation. IEEE Transactions on Big Data, 6(2), 598-608
Open this publication in new window or tab >>Nonlinear Consensus Protocols With Applications to Quantized Communication and Actuation
2019 (English)In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 6, no 2, p. 598-608Article in journal (Refereed) Published
Abstract [en]

Nonlinearities are present in all real applications. Two types of general nonlinear consensus protocols are considered in this paper, namely, the systems with nonlinear communication and actuator constraints. The solutions of the systems are understood in the sense of Filippov to handle the possible discontinuity of the controllers. For each case, we prove the asymptotic stability of the systems with minimal assumptions on the nonlinearity, for both directed and undirected graphs. These results extend the literature to more general nonlinear dynamics and topologies. As applications of established theorems, we interpret the results on quantized consensus protocols.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
Networks of autonomous agents, nonlinear systems, nonsmooth analysis, stability
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-254088 (URN)10.1109/TCNS.2018.2860461 (DOI)000469874200012 ()2-s2.0-85050615718 (Scopus ID)
Note

QC 20190625

Available from: 2019-06-25 Created: 2019-06-25 Last updated: 2019-06-25Bibliographically approved
Yi, X., Yao, L., Yang, T., George, J. & Johansson, K. H. (2018). Distributed Optimization for Second-Order Multi-Agent Systems with Dynamic Event-Triggered Communication. In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC): . Paper presented at 57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL (pp. 3397-3402). IEEE
Open this publication in new window or tab >>Distributed Optimization for Second-Order Multi-Agent Systems with Dynamic Event-Triggered Communication
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2018 (English)In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 3397-3402Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose a fully distributed algorithm for second-order continuous-time multi-agent systems to solve the distributed optimization problem. The global objective function is a sum of private cost functions associated with the individual agents and the interaction between agents is described by a weighted undirected graph. We show the exponential convergence of the proposed algorithm if the underlying graph is connected, each private cost function is locally gradient-Lipschitz- continuous, and the global objective function is restricted strongly convex with respect to the global minimizer. Moreover, to reduce the overall need of communication, we then propose a dynamic event-triggered communication mechanism that is free of Zeno behavior. It is shown that the exponential convergence is achieved if the private cost functions are also globally gradient-Lipschitz- continuous. Numerical simulations are provided to illustrate the effectiveness of the theoretical results.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-245008 (URN)10.1109/CDC.2018.8618989 (DOI)000458114803031 ()2-s2.0-85062185418 (Scopus ID)978-1-5386-1395-5 (ISBN)
Conference
57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL
Note

QC 20190305

Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-04-11Bibliographically approved
Du, W., Yi, X., George, J., Johansson, K. H. & Yang, T. (2018). Distributed Optimization with Dynamic Event-Triggered Mechanisms. In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC): . Paper presented at 57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL (pp. 969-974). IEEE
Open this publication in new window or tab >>Distributed Optimization with Dynamic Event-Triggered Mechanisms
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2018 (English)In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 969-974Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-245014 (URN)10.1109/CDC.2018.8619311 (DOI)000458114800137 ()2-s2.0-85062191415 (Scopus ID)978-1-5386-1395-5 (ISBN)
Conference
57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL
Note

QC 20190305

Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-04-11Bibliographically approved
George, J., Yi, X. & Yang, T. (2018). Distributed Robust Dynamic Average Consensus with Dynamic Event-Triggered Communication. In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC): . Paper presented at 57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL (pp. 434-439). IEEE
Open this publication in new window or tab >>Distributed Robust Dynamic Average Consensus with Dynamic Event-Triggered Communication
2018 (English)In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 434-439Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-245002 (URN)10.1109/CDC.2018.8619021 (DOI)000458114800061 ()2-s2.0-85062187680 (Scopus ID)978-1-5386-1395-5 (ISBN)
Conference
57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL
Note

QC 20190305

Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-04-11Bibliographically approved
Jafarian, M., Yi, X., Pirani, M., Sandberg, H. & Johansson, K. H. (2018). Synchronization of Kuramoto oscillators in a bidirectional frequency-dependent tree network. In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC): . Paper presented at 57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL (pp. 4505-4510). IEEE
Open this publication in new window or tab >>Synchronization of Kuramoto oscillators in a bidirectional frequency-dependent tree network
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2018 (English)In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 4505-4510Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies the synchronization of a finite number of Kuramoto oscillators in a frequency-dependent bidirectional tree network. We assume that the coupling strength of each link in each direction is equal to the product of a common coefficient and the exogenous frequency of its corresponding source oscillator. We derive a sufficient condition for the common coupling strength in order to guarantee frequency synchronization in tree networks. Moreover, we discuss the dependency of the obtained bound on both the graph structure and the way that exogenous frequencies are distributed. Further, we present an application of the obtained result by means of an event-triggered algorithm for achieving frequency synchronization in a star network assuming that the common coupling coefficient is given.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-245011 (URN)10.1109/CDC.2018.8619694 (DOI)000458114804028 ()2-s2.0-85062190796 (Scopus ID)978-1-5386-1395-5 (ISBN)
Conference
57th IEEE Conference on Decision and Control (CDC), DEC 17-19, 2018, Miami Beach, FL
Note

QC 20190305

Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-08-20Bibliographically approved
Yi, X., Lu, W. & Chen, T. (2016). Centralized Event-triggered Control for Linear Multi-agent Systems. In: PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC): . Paper presented at 28th Chinese Control and Decision Conference, MAY 28-30, 2016, Yinchuan, PEOPLES R CHINA (pp. 225-230). IEEE
Open this publication in new window or tab >>Centralized Event-triggered Control for Linear Multi-agent Systems
2016 (English)In: PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), IEEE , 2016, p. 225-230Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we study the consensus problem of linear multi-agent systems. Centralized event-triggered rules are provided so as to reduce the frequency of system's updating. The diffusion coupling feedbacks of each agent are based on the latest observations from its in-neighbours and the system's next observation time is triggered by a criterion based on all agents' information. The scenario of continuous monitoring is first considered, namely all agents' instantaneous states can be observed. It is proved that if the network topology is connected, then this centralized event-triggered coupling strategy can realize consensus exponentially for the linear multi-agent systems. Then the results are extended to discontinuous monitoring, where the system computes its next triggering time in advance without having to observe all agents' states continuously. As a special case, we apply above results to double-integrator consensus problem. One example with numerical simulation are provided to show the effectiveness of the theoretical results.

Place, publisher, year, edition, pages
IEEE, 2016
Series
Chinese Control and Decision Conference, ISSN 1948-9439
Keywords
consensus, linear multi-agent systems, centralized event-triggered, centralized self-triggered
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-242735 (URN)10.1109/CCDC.2016.7530985 (DOI)000383222300041 ()2-s2.0-84983738616 (Scopus ID)978-1-4673-9714-8 (ISBN)
Conference
28th Chinese Control and Decision Conference, MAY 28-30, 2016, Yinchuan, PEOPLES R CHINA
Note

QC 20190219

Available from: 2019-02-19 Created: 2019-02-19 Last updated: 2019-08-21Bibliographically approved
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