Exponential Input-to-State Stability for Hybrid Dynamical Networks via Impulsive Interconnection

被引:4
|
作者
Liu, Bin [1 ]
Hill, David J. [1 ,2 ]
Sun, Yunlian [3 ]
机构
[1] Australian Natl Univ, Sch Engn, GPO Box 4, Canberra, ACT 0200, Australia
[2] Natl ICT Australia, Canberra, ACT 0200, Australia
[3] Wuhan Univ, Sch Elect Engn, Wuhan 430072, Peoples R China
关键词
SMALL-GAIN THEOREM; SMOOTH LYAPUNOV FUNCTIONS; TIME-VARYING SYSTEMS; ISS SMALL-GAIN; STABILIZATION; CONNECTIONS; FEEDBACK; IISS;
D O I
10.1109/CDC.2010.5717240
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates the problem of exponential input-to-state stability (e-ISS) for hybrid dynamical networks (HDN) via impulsive interconnection. New concepts of input-to-state exponent property (IS-E) and augmented time are proposed for dynamical systems and hybrid systems respectively. By using IS-E estimations of nodes in HDN and methods such as multiple Lyapunov functions and hybrid time, two types of e-ISS criteria for continuous-time/discrete-time HDN are established respectively. The requirements on ISS property of every subsystem and small-gain condition for interconnection in interconnected systems or networks in the literature is relaxed. The obtained e-ISS results are extended to the case of delayed impulsive interconnection. One representative example is given to illustrate the theoretical results.
引用
收藏
页码:673 / 678
页数:6
相关论文
共 50 条
  • [21] Robust exponential input-to-state stability of impulsive systems with an application in micro-grids
    Liu, Bin
    Dou, Chunxia
    Hill, David J.
    SYSTEMS & CONTROL LETTERS, 2014, 65 : 64 - 73
  • [22] Exponential input-to-state stability of stochastic neural networks with mixed delays
    Yan-Jun Shu
    Xin-Ge Liu
    Feng-Xian Wang
    Sai-Bing Qiu
    International Journal of Machine Learning and Cybernetics, 2018, 9 : 807 - 819
  • [23] Exponential input-to-state stability of stochastic neural networks with mixed delays
    Shu, Yan-Jun
    Liu, Xin-Ge
    Wang, Feng-Xian
    Qiu, Sai-Bing
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2018, 9 (05) : 807 - 819
  • [24] Stabilization to Exponential Input-to-State Stability via Aperiodic Intermittent Control
    Liu, Bin
    Yang, Meng
    Liu, Tao
    Hill, David J.
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2021, 66 (06) : 2913 - 2919
  • [25] Input-to-state stability of hybrid stochastic systems with unbounded delays and impulsive effects
    Zhang, Yurong
    Yang, Zhichun
    Huang, Chuangxia
    Park, Ju H.
    NONLINEAR DYNAMICS, 2021, 104 (04) : 3753 - 3770
  • [26] Cluster synchronization analysis of complex dynamical networks by input-to-state stability
    Zhao, Junchan
    Aziz-Alaoui, M. A.
    Bertelle, Cyrille
    NONLINEAR DYNAMICS, 2012, 70 (02) : 1107 - 1115
  • [27] The Strong Integral Input-to-State Stability Property in Dynamical Flow Networks
    Nilsson, Gustav
    Coogan, Samuel
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2024, 69 (02) : 1179 - 1185
  • [28] Cluster synchronization analysis of complex dynamical networks by input-to-state stability
    Junchan Zhao
    M. A. Aziz-Alaoui
    Cyrille Bertelle
    Nonlinear Dynamics, 2012, 70 : 1107 - 1115
  • [29] Input-to-state stability of impulsive and switching hybrid systems with time-delay
    Liu, Jun
    Liu, Xinzhi
    Xie, Wei-Chau
    AUTOMATICA, 2011, 47 (05) : 899 - 908
  • [30] Input-to-state stability of hybrid stochastic systems with unbounded delays and impulsive effects
    Yurong Zhang
    Zhichun Yang
    Chuangxia Huang
    Ju H. Park
    Nonlinear Dynamics, 2021, 104 : 3753 - 3770