Structure identification of fuzzy model
Fuzzy Sets and Systems
Optimal control: linear quadratic methods
Optimal control: linear quadratic methods
Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Analysis and design of fuzzy control system
Fuzzy Sets and Systems
Analysis and design of fuzzy reduced-dimensional observer and fuzzy functional observer
Fuzzy Sets and Systems
Design of proportional parallel distributed compensators for non-linear systems
International Journal of Computer Applications in Technology
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs
IEEE Transactions on Fuzzy Systems
New approaches to relaxed quadratic stability condition of fuzzy control systems
IEEE Transactions on Fuzzy Systems
On relaxed LMI-based designs for fuzzy regulators and fuzzy observers
IEEE Transactions on Fuzzy Systems
Approaches to quadratic stability conditions and H∞ control designs for T-S fuzzy systems
IEEE Transactions on Fuzzy Systems
A new LMI-based approach to relaxed quadratic stabilization of T-S fuzzy control systems
IEEE Transactions on Fuzzy Systems
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
New approaches to H∞ controller designs based on fuzzy observers for T-S fuzzy systems via LMI
Automatica (Journal of IFAC)
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Sum-of-squares-based stability analysis of polynomial fuzzy-model-based control systems
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Quadratic stability analysis of fuzzy control systems using stepwise membership functions
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
SOS-based stability analysis of polynomial fuzzy control systems via polynomial membership functions
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
Iterative performance improvement of fuzzy control systems for three tank systems
Expert Systems with Applications: An International Journal
H∞ state feedback controller design for continuous-time T-S fuzzy systems in finite frequency domain
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
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This paper investigates the stability analysis and performance design of nonlinear systems. To facilitate the stability analysis, the Takagi-Sugeno (T-S) fuzzy model is employed to represent the nonlinear plant. Under the imperfect premise matching in which T-S fuzzy model and fuzzy controller do not share the same membership functions, a fuzzy controller with enhanced design flexibility and robustness property is proposed to control the nonlinear plant. However, the nice characteristic given by the perfect premise matching, leading to conservative stability conditions, vanishes. In this paper, under the imperfect premise matching, information of membership functions of the fuzzy model and controller are considered in stability analysis. With the introduction of slack matrices, relaxed linear matrix inequality (LMI)-based stability conditions are derived using Lyapunov-based approach. Furthermore, LMI-based performance conditions are provided to guarantee system performance. Simulation examples are given to illustrate the effectiveness of the proposed approach.