On stability and stabilization of T-S fuzzy systems with multiple random variables dependent time-varying delay

Abstract This paper is concerned with the problems of stability and stabilization for Takagi-Sugeno (T-S) fuzzy systems with multiple random variables dependent time-varying delay. Different from the previous works, we assume that probability distributions of delay in N intervals can be observed in advance. ( N - 1 ) Bernoulli distributed random variables are utilized to indicate which interval the time-varying delay falls into at a certain time instant. Then the original T-S fuzzy systems are transformed into a new model of T-S fuzzy systems with multiple random variables dependent time-varying delay, which includes the existed ones as its special cases. Based on the new model, an appropriate Lyapunov-Krasovskii (L-K) functional is constructed. Generalized Finsler’s lemma is introduced to avoid directly dealing with the interrelationship between these correlated random variables, and Reciprocally convex inequality is used to estimate integral terms from the infinitesimal operator of L-K functional. Less conservative stability criteria and stabilization conditions are proposed in the form of linear matrix inequalities (LMIs). Finally, two examples are given to demonstrate the effectiveness of the proposed methods.

[1]  Li Ma,et al.  Observer-based adaptive fuzzy tracking control of MIMO switched nonlinear systems preceded by unknown backlash-like hysteresis , 2019, Inf. Sci..

[2]  Guang-Hong Yang,et al.  H∞ filtering for T-S fuzzy systems with multiple time-varying delays: An improved delays-dependent region partitioning method , 2019, Inf. Sci..

[3]  Piyapong Niamsup,et al.  Robust Finite‐Time Control for Linear Time‐Varying Delay Systems With Bounded Control , 2016 .

[4]  Alexandre Seuret,et al.  Stability of Linear Systems With Time-Varying Delays Using Bessel–Legendre Inequalities , 2018, IEEE Transactions on Automatic Control.

[5]  Songyi Dian,et al.  Further Studies on Stability and Stabilization of T‐S Fuzzy Systems With Time‐Varying Delays via Fuzzy Lyapunov‐Krasovskii Functional Method , 2018 .

[6]  Dong Yue,et al.  Delay-Distribution-Dependent Stability and Stabilization of T–S Fuzzy Systems With Probabilistic Interval Delay , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  Yuanqing Xia,et al.  Output feedback delay compensation control for networked control systems with random delays , 2014, Inf. Sci..

[8]  Peng Shi,et al.  Consensus of Euler–Lagrange Systems Networked by Sampled-Data Information with Probabilistic Time Delays , 2015, IEEE Transactions on Cybernetics.

[9]  Lin Chen,et al.  Stability and stabilization of T-S fuzzy systems with time delay via Wirtinger-based double integral inequality , 2018, Neurocomputing.

[10]  J. Hale Functional Differential Equations , 1971 .

[11]  Chong Tan,et al.  Improved stability criteria for T–S fuzzy systems with time-varying delay via convex analysis approach , 2016 .

[12]  Dong Yue,et al.  Stabilization of Systems With Probabilistic Interval Input Delays and Its Applications to Networked Control Systems , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[13]  Hak-Keung Lam,et al.  New Stability Criterion for Continuous-Time Takagi–Sugeno Fuzzy Systems With Time-Varying Delay , 2019, IEEE Transactions on Cybernetics.

[14]  Songlin Hu,et al.  Robust H∞ control for T–S fuzzy systems with probabilistic interval time varying delay , 2012 .

[15]  Fuad E. Alsaadi,et al.  Stability analysis for discrete-time stochastic memristive neural networks with both leakage and probabilistic delays , 2018, Neural Networks.

[16]  Huanqing Wang,et al.  Adaptive neural control for non-strict-feedback nonlinear systems with input delay , 2020, Inf. Sci..

[17]  Myeong-Jin Park,et al.  Stability and Stabilization of Discrete-Time T–S Fuzzy Systems With Time-Varying Delay via Cauchy–Schwartz-Based Summation Inequality , 2017, IEEE Transactions on Fuzzy Systems.

[18]  N. Gunasekaran,et al.  Stochastic sampled‐data controller for T–S fuzzy chaotic systems and its applications , 2019, IET Control Theory & Applications.

[19]  Chen Peng,et al.  Delay-Distribution-Dependent Load Frequency Control of Power Systems With Probabilistic Interval Delays , 2016, IEEE Transactions on Power Systems.

[20]  Jianchen Liu,et al.  A generalized probability-interval-decomposition approach for stability analysis of T-S fuzzy systems with stochastic delays , 2018, J. Frankl. Inst..

[21]  Ju H. Park,et al.  Augmented Lyapunov-Krasovskii functional approaches to robust stability criteria for uncertain Takagi-Sugeno fuzzy systems with time-varying delays , 2012, Fuzzy Sets Syst..

[22]  Dong Yue,et al.  Relaxed Control Design of Discrete-Time Takagi–Sugeno Fuzzy Systems: An Event-Triggered Real-Time Scheduling Approach , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[23]  Qing-Long Han,et al.  An improved reciprocally convex inequality and an augmented Lyapunov-Krasovskii functional for stability of linear systems with time-varying delay , 2017, Autom..

[24]  Feiqi Deng,et al.  Modeling and Control of Itô Stochastic Networked Control Systems With Random Packet Dropouts Subject to Time-Varying Sampling , 2017, IEEE Transactions on Automatic Control.

[25]  Dong Yue,et al.  Relaxed Real-Time Scheduling Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems via An Alterable-Weights-Based Ranking Switching Mechanism , 2018, IEEE Transactions on Fuzzy Systems.

[26]  Xiefu Jiang,et al.  On sampled-data fuzzy control design approach for T-S model-based fuzzy systems by using discretization approach , 2015, Inf. Sci..

[27]  Dianhui Wang,et al.  Quadratically convex combination approach to stability of T-S fuzzy systems with time-varying delay , 2014, J. Frankl. Inst..

[28]  Vladimir L. Kharitonov,et al.  Stability of Time-Delay Systems , 2003, Control Engineering.

[29]  Chao Lu,et al.  Mathematical expectation modeling of wide-area controlled power systems with stochastic time delay , 2015, 2015 IEEE Power & Energy Society General Meeting.

[30]  Qing-Long Han,et al.  Robust $H_{\infty}$ Control for Uncertain Takagi–Sugeno Fuzzy Systems With Interval Time-Varying Delay , 2007, IEEE Transactions on Fuzzy Systems.

[31]  H. Trinh,et al.  Refined Jensen-based inequality approach to stability analysis of time-delay systems , 2015 .

[32]  Bing Chen,et al.  A novel Lyapunov-Krasovskii functional approach to stability and stabilization for T-S fuzzy systems with time delay , 2018, Neurocomputing.

[33]  Xuerong Mao,et al.  Exponential stability of stochastic delay interval systems with Markovian switching , 2002, IEEE Trans. Autom. Control..

[34]  Ju H. Park,et al.  Stability and stabilization of T-S fuzzy systems with time-varying delays via augmented Lyapunov-Krasovskii functionals , 2016, Inf. Sci..

[35]  Frédéric Gouaisbaut,et al.  Wirtinger-based integral inequality: Application to time-delay systems , 2013, Autom..

[36]  Alireza Alfi,et al.  Finite-time $${{H}_{\infty }}$$H∞ stability analysis of uncertain network-based control systems under random packet dropout and varying network delay , 2017 .

[37]  PooGyeon Park,et al.  Auxiliary function-based integral inequalities for quadratic functions and their applications to time-delay systems , 2015, J. Frankl. Inst..

[38]  Xiuxia Yin,et al.  Further results on memory control of nonlinear discrete-time networked control systems with random input delay , 2014 .

[39]  PooGyeon Park,et al.  Reciprocally convex approach to stability of systems with time-varying delays , 2011, Autom..

[40]  Wei Xing Zheng,et al.  A new result on stability analysis for stochastic neutral systems , 2010, Autom..

[41]  Derui Ding,et al.  An overview of recent developments in Lyapunov-Krasovskii functionals and stability criteria for recurrent neural networks with time-varying delays , 2018, Neurocomputing.

[42]  Songyi Dian,et al.  Stability and stabilization of T-S fuzzy systems with two additive time-varying delays , 2019, Inf. Sci..

[43]  Huanqing Wang,et al.  Finite-time adaptive fault-tolerant control for nonlinear systems with multiple faults , 2019, IEEE/CAA Journal of Automatica Sinica.