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
来源：
49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2010年
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
  • [31] 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
  • [32] Input-to-state stability analysis of impulsive stochastic neural networks based on average impulsive interval
    Yao, Fengqi
    Cao, Jinde
    Qiu, Li
    Cheng, Pei
    2015 34TH CHINESE CONTROL CONFERENCE (CCC), 2015, : 1775 - 1780
  • [33] Input-to-state dynamical stability of interconnected systems
    Dashkovskiy, Sergey N.
    Naujok, Lars
    PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009), 2009, : 1411 - 1416
  • [34] Exponential Stability and Input-to-State Stability of Polynomial Systems via an Observer with Sporadic Measurements
    Cai, Xu
    Lou, Xuyang
    Sid, Mohanmed Amine
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2025,
  • [35] Exponential input-to-state stability of stochastic fuzzy delayed Cohen-Grossberg neural networks under impulsive perturbations
    Zhou, Weisong
    Zeng, Hao
    Wu, Donghai
    2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 1291 - 1296
  • [36] Lyapunov conditions for input-to-state stability of impulsive systems
    Hespanha, Joao P.
    Liberzon, Daniel
    Teel, Andrew R.
    AUTOMATICA, 2008, 44 (11) : 2735 - 2744
  • [37] State estimation and input-to-state stability of impulsive stochastic BAM neural networks with mixed delays
    Li, Jianjun
    Zhou, Weisong
    Yang, Zhichun
    NEUROCOMPUTING, 2017, 227 : 37 - 45
  • [38] Input-to-State Stability for Dynamical Neural Networks with Time-Varying Delays
    Zhou, Weisong
    Yang, Zhichun
    ABSTRACT AND APPLIED ANALYSIS, 2012,
  • [39] On the pth moment integral input-to-state stability and input-to-state stability criteria for impulsive stochastic functional differential equations
    Hu, Wei
    Zhu, Quanxin
    Karimi, Hamid Reza
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2019, 29 (16) : 5609 - 5620
  • [40] Exponential input-to-state stability of composite stochastic systems
    Fakhreddin Abedi
    Wah June Leong
    Sarkhosh Seddighi Chaharborj
    Advances in Difference Equations, 2013
12345