Dissipative Tracking Control of Nonlinear Markov Jump Systems With Incomplete Transition Probabilities: A Multiple-Event-Triggered Approach

被引:17
作者
Ran, Guangtao [1 ,2 ]
Shu, Zhan [2 ]
Lam, Hak-Keung [3 ]
Liu, Jian [4 ]
Li, Chuanjiang [1 ]
机构
[1] Harbin Inst Technol, Dept Control Sci & Engn, Harbin 150001, Peoples R China
[2] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G IH9, Canada
[3] Kings Coll London, Dept Engn, London WC2R 2LS, England
[4] Southeast Univ, Sch Automat, Nanjing 210096, Peoples R China
基金
中国国家自然科学基金;
关键词
Adaptive event-triggered scheme (AETS); incomplete transition probabilities; Markov jump systems (M[!text type='JS']JS[!/text]s); multiple-event-triggered; OUTPUT-FEEDBACK CONTROL; STABILITY ANALYSIS; DYNAMICAL-SYSTEMS; LINEAR-SYSTEMS; FUZZY;
D O I
10.1109/TFUZZ.2022.3225672
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article deals with the problem of multiple-event-triggered dissipative tracking control for nonlinear Markov jump systems with incomplete transition probabilities. An interval type-2 fuzzy model with partially known transition probability matrix is used to capture the underlying nonlinearities and a hidden Markov model with an incomplete conditional probability matrix is employed to describe the possible asynchronous phenomenon between the plant and the tracking controller. A multiple-event-triggered methodology involving two adaptive event-triggered schemes for the actuator channel and the sensor channel is proposed. By using the Lyapunov and dissipativity theory, sufficient conditions for the desired tracking controller are established in terms of linear matrix inequalities. Last, two examples, involving one numerical and one practical model named the Henon system, are utilized to show the effectiveness of the proposed tracking control algorithm.
引用
收藏
页码:2389 / 2400
页数:12
相关论文
共 40 条
[1]   Modified repetitive periodic event-triggered control with equivalent-input-disturbance for linear systems subject to unknown disturbance [J].
Abd-Elhaleem, Sameh ;
Soliman, Mohamed ;
Hamdy, Mohamed .
INTERNATIONAL JOURNAL OF CONTROL, 2022, 95 (07) :1825-1837
[2]   Output feedback control of Markov jump linear systems in continuous-time [J].
de Farias, DP ;
Geromel, JC ;
do Val, JBR ;
Costa, OLV .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2000, 45 (05) :944-949
[3]   Asynchronous Control of Continuous-Time Nonlinear Markov Jump Systems Subject to Strict Dissipativity [J].
Dong, Shanling ;
Wu, Zheng-Guang ;
Su, Hongye ;
Shi, Peng ;
Karimi, Hamid Reza .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2019, 64 (03) :1250-1256
[4]   Quantized Control of Markov Jump Nonlinear Systems Based on Fuzzy Hidden Markov Model [J].
Dong, Shanling ;
Wu, Zheng-Guang ;
Shi, Peng ;
Su, Hongye ;
Huang, Tingwen .
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 49 (07) :2420-2430
[5]   H∞ tracking control of nonlinear networked systems with a novel adaptive event-triggered communication [J].
Gu, Zhou ;
Yue, Dong ;
Liu, Jinliang ;
Ding, Zhentao .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2017, 354 (08) :3540-3553
[6]   Adaptive Event-Triggered Fault Detection for Interval Type-2 T-S Fuzzy Systems With Sensor Saturation [J].
Guo, Xiang-Gui ;
Fan, Xiao ;
Ahn, Choon Ki .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (08) :2310-2321
[7]   Adaptive Fuzzy Predictive Controller for a Class of Networked Nonlinear Systems With Time-Varying Delay [J].
Hamdy, Mohamed ;
Abd-Elhaleem, Sameh ;
Fkirin, M. A. .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (04) :2135-2144
[8]   Attack-Resilient Event-Triggered Fuzzy Interval Type-2 Filter Design for Networked Nonlinear Systems Under Sporadic Denial-of-Service Jamming Attacks [J].
Hu, Songlin ;
Yue, Dong ;
Dou, Chunxia ;
Xie, Xiangpeng ;
Ma, Yong ;
Ding, Lei .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (01) :190-204
[9]   Stability analysis of interval type-2 fuzzy-model-based control systems [J].
Lam, H. K. ;
Seneviratne, Lakmal D. .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2008, 38 (03) :617-628
[10]   A review on stability analysis of continuous-time fuzzy-model-based control systems: From membership-function-independent to membership-function-dependent analysis [J].
Lam, H. K. .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 67 :390-408