Optimal and event-based networked control of physically interconnected systems and multi-agent systems

被引:16
|
作者
Demir, Ozan [1 ]
Lunze, Jan [1 ]
机构
[1] Ruhr Univ Bochum, Inst Automat & Comp Control, Bochum, Germany
关键词
networked control; decomposition methods; event-based control; LQR design; distributed controller; DISTRIBUTED CONTROL; DESIGN;
D O I
10.1080/00207179.2013.825816
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many interconnected systems like vehicle platoons or energy networks consist of similar or identical subsystems. The subsystem interconnections are either caused by the physical relations among the subsystems or have to be introduced by the controller to cope with cooperative control goals. This paper proposes strategies to reduce the complexity of the controller design problem (offline information reduction) and to reduce the amount of the system information, which is necessary for the implementation of the designed controller (online information reduction). It consists of two parts. The first part deals with the linear quadratic regulator (LQR) design problem for interconnected systems. A decomposition based on a state transformation is introduced, which allows to design the optimal controller for the interconnected system by considering modified subsystems separately. The proposed decomposition approach can be uniformly applied to multi-agent systems and physically interconnected systems.The second part of the paper introduces an event-based control strategy for multi-agent systems. The event-based control is a means to reduce the communication effort by invoking an information exchange among the subsystems only when the deviation between the estimated and current subsystem state exceeds an event threshold. An event-based controller is proposed, which mimics the continuous state-feedback controller with a desired precision. The relation between the event threshold and the approximation error is analysed.
引用
收藏
页码:169 / 185
页数:17
相关论文
共 50 条
  • [31] H∞ CONTROL OF NETWORKED MULTI-AGENT SYSTEMS
    Zhongkui LI Zhisheng DUAN Lin HUANG State Key Lab for Turbulence and Complex Systems and Department of Mechanics and Aerospace Engineering
    Journal of Systems Science & Complexity, 2009, 22 (01) : 35 - 48
  • [32] H∞ control of networked multi-agent systems
    Zhongkui Li
    Zhisheng Duan
    Lin Huang
    Journal of Systems Science and Complexity, 2009, 22 : 35 - 48
  • [33] On Designing Event-Based Consensus Protocols for Nonlinear Multi-Agent Systems
    Ge, Xiaohua
    Han, Qing-Long
    PROCEEDINGS OF THE IECON 2016 - 42ND ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2016, : 5392 - 5397
  • [34] Blending Event-Based and Multi-Agent Systems Around Coordination Abstractions
    Omicini, Andrea
    Fortino, Giancarlo
    Mariani, Stefano
    COORDINATION MODELS AND LANGUAGES, COORDINATION 2015, 2015, 9037 : 186 - 193
  • [35] H∞ consensus of event-based multi-agent systems with switching topology
    Zhang, Hao
    Yang, Ruohan
    Yan, Huaicheng
    Yang, Fuwen
    INFORMATION SCIENCES, 2016, 370 : 623 - 635
  • [36] Event-based consensus of multi-agent systems with general linear models
    Zhu, Wei
    Jiang, Zhong-Ping
    Feng, Gang
    AUTOMATICA, 2014, 50 (02) : 552 - 558
  • [37] Optimal weights for consensus of networked multi-agent systems
    Li, Xiang-Shun
    Fang, Hua-Jing
    Information Technology Journal, 2009, 8 (01) : 77 - 82
  • [38] Optimal Synchronization of Circulant Networked Multi-Agent Systems
    Mosebach, Andrej
    Lunze, Jan
    2013 EUROPEAN CONTROL CONFERENCE (ECC), 2013, : 3815 - 3820
  • [39] Event-triggered communication and control of networked systems for multi-agent consensus
    Nowzari, Cameron
    Garcia, Eloy
    Cortes, Jorge
    AUTOMATICA, 2019, 105 : 1 - 27
  • [40] Dynamic Event-Based Control for Stochastic Optimal Regulation of Nonlinear Networked Control Systems
    Ming, Zhongyang
    Zhang, Huaguang
    Luo, Yanhong
    Wang, Wei
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (10) : 7299 - 7308