Robust control of a class of uncertain nonlinear systems
Systems & Control Letters
An LMI-based H∞ fuzzy control system design with TS framework
Information Sciences: an International Journal - Special issue analytical theory of fuzzy control with applications
H∞ control of uncertain fuzzy continuous-time systems
Fuzzy Sets and Systems
Robust fuzzy H∞ control for uncertain nonlinear systems via state feedback: an LMI approach
Fuzzy Sets and Systems
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
An approach to H∞ control of fuzzy dynamic systems
Fuzzy Sets and Systems - Theme: Modeling and control
Improved H∞ control of discrete-time fuzzy systems: a cone complementarity linearization approach
Information Sciences: an International Journal
H∞ fuzzy output feedback control design for nonlinear systems: an LMI approach
IEEE Transactions on Fuzzy Systems
A multiple Lyapunov function approach to stabilization of fuzzy control systems
IEEE Transactions on Fuzzy Systems
Fuzzy guaranteed cost control for nonlinear systems with time-varying delay
IEEE Transactions on Fuzzy Systems
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Stabilization of Nonlinear Systems Under Variable Sampling: A Fuzzy Control Approach
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
Hi-index | 0.00 |
This paper focuses on the problem of Guaranteed cost control of uncertain T-S fuzzy systems. Based on observer design, the guaranteed cost output feedback control law which guarantees that the closed-loop uncertain T-S fuzzy system is robustly asymptotically stable is proposed. By utilizing the Lyapunov function together with the linear matrix inequality (LMI) approach and free weighting matrix method, some sufficient conditions are obtained, which guarantee the asymptotic stability of uncertain T-S fuzzy systems. A numerical example is included to show the proposed method is effective and can provide less conservative results.