Relaxed stability criteria for discrete-time Takagi-Sugeno fuzzy systems via new augmented nonquadratic Lyapunov functions

The problem of relaxed stability analysis of discrete-time Takagi-Sugeno fuzzy systems is investigated in this paper. Different from those existing results in the literature that are only quadratic parameter dependent on system state variables, a new augmented nonquadratic Lyapunov function, which is formulated in a higher order form of system state variables than those existing results, is developed for achieving the task of stability analysis with less conservatism. More importantly, it can be proved that the approach proposed in this paper contains the existing one as a special case. Finally, the effectiveness of the proposed approach is illustrated by means of numerical experiments. HighlightsAn augmented nonquadratic Lyapunov function is proposed.The criterion takes the form of an LMI which is computationally tractable.The obtained stability criteria are less conservative.The existing results are special cases of ours.

[1]  Ricardo C. L. F. Oliveira,et al.  Parameter-Dependent LMIs in Robust Analysis: Characterization of Homogeneous Polynomially Parameter-Dependent Solutions Via LMI Relaxations , 2007, IEEE Transactions on Automatic Control.

[2]  Hak-Keung Lam,et al.  Quadratic-Stability Analysis of Fuzzy-Model-Based Control Systems Using Staircase Membership Functions , 2010, IEEE Transactions on Fuzzy Systems.

[3]  Huaguang Zhang,et al.  Fuzzy $H_\infty$ Filter Design for a Class of Nonlinear Discrete-Time Systems With Multiple Time Delays , 2007, IEEE Transactions on Fuzzy Systems.

[4]  Dong Yue,et al.  Further Studies on Control Synthesis of Discrete-Time T-S Fuzzy Systems via Augmented Multi-Indexed Matrix Approach , 2014, IEEE Transactions on Cybernetics.

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

[6]  Xiangpeng Xie,et al.  Control synthesis of Roesser type discrete-time 2-D T-S fuzzy systems via a multi-instant fuzzy state-feedback control scheme , 2015, Neurocomputing.

[7]  Guang-Hong Yang,et al.  $H_{\infty}$ Controller Synthesis via Switched PDC Scheme for Discrete-Time T--S Fuzzy Systems , 2009, IEEE Transactions on Fuzzy Systems.

[8]  Yung-Sheng Liu,et al.  A new LMI-based approach to relaxed quadratic stabilization of T-S fuzzy control systems , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[9]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  Xiangpeng Xie,et al.  An efficient approach for reducing the conservatism of LMI-based stability conditions for continuous-time T-S fuzzy systems , 2015, Fuzzy Sets Syst..

[11]  Huaguang Zhang,et al.  Delay-Dependent Guaranteed Cost Control for Uncertain Stochastic Fuzzy Systems With Multiple Time Delays , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[12]  Baocang Ding,et al.  Stabilization of Takagi–Sugeno Model via Nonparallel Distributed Compensation Law , 2008, IEEE Transactions on Fuzzy Systems.

[13]  Jun Yang,et al.  Fuzzy Model-Based Robust Networked Control for a Class of Nonlinear Systems , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[14]  Fernando de Oliveira Souza,et al.  Reducing conservativeness in recent stability conditions of TS fuzzy systems , 2009, Autom..

[15]  Xiangpeng Xie,et al.  Control Synthesis of Discrete-Time T–S Fuzzy Systems Based on a Novel Non-PDC Control Scheme , 2013, IEEE Transactions on Fuzzy Systems.

[16]  Xiangpeng Xie,et al.  Observer Design of Discrete-Time T–S Fuzzy Systems Via Multi-Instant Homogenous Matrix Polynomials , 2014, IEEE Transactions on Fuzzy Systems.

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

[18]  Baocang Ding,et al.  Homogeneous Polynomially Nonquadratic Stabilization of Discrete-Time Takagi–Sugeno Systems via Nonparallel Distributed Compensation Law , 2010, IEEE Transactions on Fuzzy Systems.

[19]  Xiangpeng Xie,et al.  Relaxed observer design of discrete-time T-S fuzzy systems via a novel multi-instant fuzzy observer , 2014, Signal Process..

[20]  Shaocheng Tong,et al.  H∞ control design for discrete-time switched fuzzy systems , 2015, Neurocomputing.

[21]  Xiao‐Heng Chang A Descriptor Representation Approach , 2012 .

[22]  Geraldo Nunes Silva,et al.  Reducing the conservatism of LMI-based stabilisation conditions for TS fuzzy systems using fuzzy Lyapunov functions , 2013, Int. J. Syst. Sci..

[23]  Guang-Hong Yang,et al.  Relaxed stabilization conditions for continuous-time Takagi-Sugeno fuzzy control systems , 2010, Inf. Sci..

[24]  Shaocheng Tong,et al.  Homogenous Polynomially Parameter-Dependent $H_{ \infty}$ Filter Designs of Discrete-Time Fuzzy Systems , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[25]  Yuanchun Li,et al.  Reliable observer-based H∞ control for discrete-time fuzzy systems with time-varying delays and stochastic actuator faults via scaled small gain theorem , 2015, Neurocomputing.