Imperfect premise matching controller design for T-S fuzzy systems under network environments

A general diagram is proposed to deal with unmatch premises of T-S fuzzy systems under network environments.A less conservative stability criterion is obtained by use of the Wirtinger-based inequality technique to deal with the cross items in the derivation of the main results.A novel imperfect premise matching design method is utilized to enhance the design flexibility for the T-S fuzzy systems under network environments. This paper focuses on an imperfect premise matching controller design for T-S fuzzy systems under network environments. Different with the traditional parallel distribution compensation (PDC) method, the same premises between the PDC controller and the T-S fuzzy systems are no longer needed again in the proposed method. Under consideration of the unmatched grades of membership in the networked T-S fuzzy systems, a unified T-S fuzzy model is firstly proposed, in which a networked state-feedback fuzzy controller with communication delays is used to reconstruct the system. Then, based on the constructed model and by use of the Wirtinger-based inequality technique to deal with the cross items, two less conservative stability and stabilization criteria are derived to enhance the design flexibility. Finally, two numerical examples are used to show the effectiveness of proposed method.

[1]  Jun Yang,et al.  T-S Fuzzy-Model-Based Robust $H_{\infty}$ Design for Networked Control Systems With Uncertainties , 2007, IEEE Transactions on Industrial Informatics.

[2]  Hamid Reza Karimi,et al.  Novel Stability Criteria for T--S Fuzzy Systems , 2014, IEEE Transactions on Fuzzy Systems.

[3]  Rodolfo E. Haber,et al.  An optimal fuzzy control system in a network environment based on simulated annealing. An application to a drilling process , 2009, Appl. Soft Comput..

[4]  R. Rovatti,et al.  On the approximation capabilities of the homogeneous Takagi-Sugeno model , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[5]  Hak-Keung Lam,et al.  LMI-based Stability and Performance Design of Fuzzy Control Systems: Fuzzy Models and Controllers with Different Premises , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[6]  Dong Yue,et al.  To Transmit or Not to Transmit: A Discrete Event-Triggered Communication Scheme for Networked Takagi–Sugeno Fuzzy Systems , 2013, IEEE Transactions on Fuzzy Systems.

[7]  Dong Yue,et al.  Delay Distribution-Dependent Control for Networked Takagi–Sugeno Fuzzy Systems , 2015 .

[8]  Kai Zenger,et al.  Delay-Dependent Stability Analysis of Uncertain Fuzzy Systems with State and Input Delays under Imperfect Premise Matching , 2013 .

[9]  Minrui Fei,et al.  On hold or drop out-of-order packets in networked control systems , 2014, Inf. Sci..

[10]  Xianlin Huang,et al.  New delay-dependent robust stability and stabilization for uncertain T-S fuzzy time-delay systems under imperfect premise matching , 2012 .

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

[12]  Ligang Wu,et al.  Fuzzy Tracking Control for Nonlinear Networked Systems , 2017, IEEE Transactions on Cybernetics.

[13]  Xiaozhan Yang,et al.  Stability and Stabilization of Discrete-Time T–S Fuzzy Systems With Stochastic Perturbation and Time-Varying Delay , 2014, IEEE Transactions on Fuzzy Systems.

[14]  G. Feng,et al.  A Survey on Analysis and Design of Model-Based Fuzzy Control Systems , 2006, IEEE Transactions on Fuzzy Systems.

[15]  Guanrong Chen,et al.  A modified fuzzy PI controller for a flexible-joint robot arm with uncertainties , 2001, Fuzzy Sets Syst..

[16]  E. Tissir,et al.  Delay Dependent Robust Stability of T-S Fuzzy Systems with Additive Time Varying Delays , 2012 .

[17]  Jun Yoneyama,et al.  Robust guaranteed cost control of uncertain fuzzy systems under time-varying sampling , 2011, Appl. Soft Comput..

[18]  Ligang Wu,et al.  Event-Triggered Control for Nonlinear Systems Under Unreliable Communication Links , 2017, IEEE Transactions on Fuzzy Systems.

[19]  Bo Shen,et al.  Fuzzy-Logic-Based Control, Filtering, and Fault Detection for Networked Systems: A Survey , 2015 .

[20]  Wen-Jer Chang,et al.  Intelligent fuzzy control with imperfect premise matching concept for complex nonlinear multiplicative noised systems , 2015, Neurocomputing.

[21]  Nong Zhang,et al.  Application of evolving Takagi-Sugeno fuzzy model to nonlinear system identification , 2008, Appl. Soft Comput..

[22]  Jianbin Qiu,et al.  A novel dropout compensation scheme for control of networked T-S fuzzy dynamic systems , 2014, Fuzzy Sets Syst..

[23]  Yuechao Ma,et al.  Delay-dependent robust H∞ filter for T-S fuzzy time-delay systems with exponential stability , 2013 .

[24]  Dong Yue,et al.  Output Feedback Control of Discrete-Time Systems in Networked Environments , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

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

[26]  James Lam,et al.  Stabilization of Networked Control Systems With a Logic ZOH , 2009, IEEE Transactions on Automatic Control.

[27]  Hak-Keung Lam,et al.  Stability Analysis of Polynomial-Fuzzy-Model-Based Control Systems With Mismatched Premise Membership Functions , 2014, IEEE Transactions on Fuzzy Systems.

[28]  J. Humberto Pérez-Cruz,et al.  Evolving intelligent system for the modelling of nonlinear systems with dead-zone input , 2014, Appl. Soft Comput..

[29]  Kazuo Tanaka,et al.  Dynamic parallel distributed compensation for Takagi-Sugeno fuzzy systems: An LMI approach , 2000, Inf. Sci..

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

[31]  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.

[32]  Dong Yue,et al.  Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model , 2015, Appl. Soft Comput..

[33]  Chen Peng,et al.  Communication-Delay-Distribution-Dependent Networked Control for a Class of T–S Fuzzy Systems , 2010, IEEE Transactions on Fuzzy Systems.

[34]  Qing-Long Han,et al.  On Designing Fuzzy Controllers for a Class of Nonlinear Networked Control Systems , 2008, IEEE Transactions on Fuzzy Systems.

[35]  Dong Yue,et al.  Network-based robust H ∞ control of systemswith uncertainty , 2005 .

[36]  Hak-Keung Lam,et al.  Stability Analysis and Performance Design for Fuzzy-Model-Based Control System Under Imperfect Premise Matching , 2009, IEEE Transactions on Fuzzy Systems.

[37]  Minrui Fei,et al.  Networked control for a class of T-S fuzzy systems with stochastic sensor faults , 2013, Fuzzy Sets Syst..