Distributed Control Under Transmission Delays: A Model-Based Hybrid System Approach

被引:0
作者
Dhullipalla, Mani H. [1 ]
Yu, Hao [2 ]
Chen, Tongwen [1 ]
机构
[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 1G4, Canada
[2] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
基金
加拿大自然科学与工程研究理事会;
关键词
Delays; Protocols; Mathematical models; Indexes; Context modeling; Nonlinear dynamical systems; Decentralized control; Model-based approach; multiagent systems (MASs); networked control systems (NCSs); small transmission delays; NETWORKED CONTROL-SYSTEMS; EVENT-TRIGGERED CONTROL; SAMPLED-DATA STABILIZATION; STABILITY;
D O I
10.1109/TAC.2024.3401970
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Networked systems, in practice, suffer from several network-induced imperfections. In this article, we consider the problem of distributed control of nonlinear multiagent systems (MASs) where the information broadcasts over a network are susceptible to one such imperfection, namely, transmission delays. The design methodology employed is such that the sampling instants (at which agents broadcast information) could be both aperiodic and asynchronous in nature. The broadcasts, upon arrival, are propagated by the agents through dynamical models and these propagates are used in their control protocols. The overall MAS is formulated as a hybrid dynamical system whose stability governs the upper bounds on: first, the sampling interval, namely, the duration between two consecutive broadcasts, and second, the transmission delays that the broadcasts might be prone to. Finally, through a case study on the consensus of Lipschitz nonlinear agents, we demonstrate the effectiveness of the proposed methodology.
引用
收藏
页码:7901 / 7908
页数:8
相关论文
共 27 条
  • [1] Ge X., Han Q.-L., Ding D., Zhang X., Ning B., A survey on recent advances in distributed sampled-data cooperative control of multi-agent systems, Neurocomputing, 275, pp. 1684-1701, (2018)
  • [2] Hespanha J.P., Naghshtabrizi P., Xu Y., A survey of recent results in networked control systems, Proc. IEEE Proc. IRE, 95, 1, pp. 138-162, (2007)
  • [3] Zhang X.-M., Et al., Networked control systems: A survey of trends and techniques, IEEE/CAA J. Automatica Sinica, 7, 1, pp. 1-17, (2020)
  • [4] Gao H., Chen T., Lam J., A new delay system approach to networkbased control, Automatica, 44, 1, pp. 39-52, (2008)
  • [5] Naghshtabrizi P., Hespanha J.P., Teel A.R., Stability of delay impulsive systems with application to networked control systems, Trans. Inst. Meas. Control, 32, 5, pp. 511-528, (2010)
  • [6] Yu M., Wang L., Chu T., Sampled-data stabilisation of networked control systems with nonlinearity, IEE Proc.-Control Theory Appl., 152, 6, pp. 609-614, (2005)
  • [7] Cao J., Zhong S., Hu Y., Novel delay-dependent stability conditions for a class of MIMO networked control systems with nonlinear perturbation, Appl. Math. Computation, 197, 2, pp. 797-809, (2008)
  • [8] Polushin I.G., Marquez H.J., Multirate versions of sampleddata stabilization of nonlinear systems, Automatica, 40, 6, pp. 1035-1041, (2004)
  • [9] Nesic D., Teel A.R., Kokotovic P.V., Sufficient conditions for stabilization of sampled-data nonlinear systems via discrete-time approximations, Syst. Control Lett., 38, 4-5, pp. 259-270, (1999)
  • [10] Heemels W.P.M.H., Teel A.R., Van De Wouw N., Nesic D., Networked control systems with communication constraints: Tradeoffs between transmission intervals, delays and performance, IEEE Trans. Autom. control, 55, 8, pp. 1781-1796, (2010)