Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Computers & Mathematics with Applications
Robust H∞ control for discrete-time fuzzy systems via basis-dependent Lyapunov functions
Information Sciences: an International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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
Robust H∞ disturbance attenuation for a class of uncertain discrete-time fuzzy systems
IEEE Transactions on Fuzzy Systems
New approaches to relaxed quadratic stability condition of fuzzy control systems
IEEE Transactions on Fuzzy Systems
Parameterized linear matrix inequality techniques in fuzzy control system design
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
On relaxed LMI-based designs for fuzzy regulators and fuzzy observers
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
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
New approaches to H∞ controller designs based on fuzzy observers for T-S fuzzy systems via LMI
Automatica (Journal of IFAC)
Fuzzy modeling and H∞ control for general 2D nonlinear systems
Fuzzy Sets and Systems
H∞ state feedback controller design for continuous-time T-S fuzzy systems in finite frequency domain
Information Sciences: an International Journal
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In this study, we establish a less-conservative H∞ stabilization condition for a class of discrete-time Takagi-Sugeno (T-S) fuzzy systems. To this end, we propose a useful relaxation technique that can be used to transform parameterized-linear-matrix inequalities (PLMIs) with homogeneous polynomial dependence on current-time parameters and preceding parameters into a finite set of LMIs. The main feature of this technique is that all possible slack variables can be included in the relaxation process to fully exploit the convexity of the PLMIs. By applying the relaxation technique, we establish a less-conservative LMI-based H∞ stabilization condition.