Control Synthesis of Markovian Jump Nonlinear System via A New Fuzzy Switching Controller

The task of control synthesis of Markovian jump nonlinear system is well investigated through giving a new fuzzy switching controller aiming at easing the conservatism than before. Compared with previous results, less conservative stabilization conditions for the considered discrete-time Markovian jump fuzzy system can be gained which lead to wider application of the proposed theoretical method. In the analysis and derivation process, some important information hidden in the fuzzy basis function is well utilized and thus a new scheme of fuzzy switching control law is presented to reduce the conservatism that is caused by ignoring those important information hidden in the fuzzy basis function in the literature. Finally, the validity and advantage of the proposed method over the recent one is also demonstrated by controlling an inverted pendulum model.

[1]  Yan Liang,et al.  Target State and Markovian Jump Ionospheric Height Bias Estimation for OTHR Tracking Systems , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[2]  Qing-Long Han,et al.  Distributed sampled-data asynchronous H∞ filtering of Markovian jump linear systems over sensor networks , 2016, Signal Process..

[3]  Peng Yang,et al.  Further studies on LMI-based relaxed stabilization conditions for nonlinear systems in Takagi-Sugeno's form , 2006, Autom..

[4]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[5]  N. Gunasekaran,et al.  State estimation of T-S fuzzy delayed neural networks with Markovian jumping parameters using sampled-data control , 2017, Fuzzy Sets Syst..

[6]  Fei Liu,et al.  H∞ control for fuzzy Markovian jump systems based on fuzzy Lyapunov function , 2017, 2017 36th Chinese Control Conference (CCC).

[7]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[8]  Thierry-Marie Guerra,et al.  LMI-based relaxed nonquadratic stabilization conditions for nonlinear systems in the Takagi-Sugeno's form , 2004, Autom..

[9]  Sung Hyun Kim Relaxed nonquadratic stabilization conditions for Markovian jump fuzzy systems with incomplete transition descriptions , 2016, J. Frankl. Inst..

[10]  Hamid Reza Karimi,et al.  Stability analysis and controller design for a class of T-S fuzzy Markov jump system with uncertain expectation of packet dropouts , 2013, 2013 American Control Conference.

[11]  Shuping Ma,et al.  Robust output feedback stabilization for uncertain discrete-time Markov jump singular systems , 2009, 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[12]  E. Boukas,et al.  H∞ control for discrete‐time Markovian jump linear systems with partly unknown transition probabilities , 2009 .

[13]  Young Hoon Joo,et al.  Robust H∞ control for uncertain nonlinear active magnetic bearing systems via Takagi-Sugeno fuzzy models , 2010 .

[14]  M. Syed Ali,et al.  Finite-time H∞ control for a class of Markovian jumping neural networks with distributed time varying delays-LMI approach , 2018 .

[15]  R. Rakkiyappan,et al.  Leakage-delay-dependent stability analysis of Markovian jumping linear systems with time-varying delays and nonlinear perturbations , 2016 .

[16]  Bing Chen,et al.  Robust Stability for Uncertain Delayed Fuzzy Hopfield Neural Networks With Markovian Jumping Parameters , 2009, IEEE Trans. Syst. Man Cybern. Part B.

[17]  Sung Hyun Kim,et al.  ${\cal H}_\infty$ State-Feedback-Control Design for Discrete-Time Fuzzy Systems Using Relaxation Technique for Parameterized LMI , 2010, IEEE Transactions on Fuzzy Systems.

[18]  Huai-Ning Wu,et al.  H∞ fuzzy control design of discrete‐time nonlinear active fault‐tolerant control systems , 2009 .

[19]  M. Syed Ali,et al.  Passivity analysis of stochastic neural networks with leakage delay and Markovian jumping parameters , 2016, Neurocomputing.

[20]  Qingling Zhang,et al.  Delay-dependent H∞ control for a class of uncertain time-delay singular Markovian jump systems via hybrid impulsive control , 2016 .

[21]  Peng Shi,et al.  Dissipativity-Based Reliable Control for Fuzzy Markov Jump Systems With Actuator Faults , 2017, IEEE Transactions on Cybernetics.

[22]  Pierre Apkarian,et al.  Parameterized linear matrix inequality techniques in fuzzy control system design , 2001, IEEE Trans. Fuzzy Syst..

[23]  Dong Yue,et al.  Control Synthesis of Discrete-Time T–S Fuzzy Systems via a Multi-Instant Homogenous Polynomial Approach , 2016, IEEE Transactions on Cybernetics.