An anti-windup design for linear systems with input saturation
Automatica (Journal of IFAC)
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
International Journal of Systems Science - Special issue: Anti-windup
Information Sciences: an International Journal
Information Sciences: an International Journal
Adaptive output feedback control of nonlinear systems with actuator failures
Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Delay-dependent guaranteed cost control for T-S fuzzy systems with time delays
IEEE Transactions on Fuzzy Systems
Delay-Dependent Robust Control for T–S Fuzzy Systems With Time Delay
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Brief Multivariable anti-windup controller synthesis using linear matrix inequalities
Automatica (Journal of IFAC)
Technical communique: Robust stabilization of uncertain systems with unknown input delay
Automatica (Journal of IFAC)
State estimation with asynchronous multi-rate multi-smart sensors
Information Sciences: an International Journal
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This study presents a robust anti-windup fuzzy control approach for uncertain nonlinear time-delay systems with actuator saturations. The discussed system dynamics is presented by the Takagi-Sugeno (T-S) fuzzy model. To facilitate the design process, the nonlinearity of input saturation is characterized by a specific sector condition. Given a stabilizing dynamic output feedback fuzzy controller, an anti-windup control approach is then developed to maximize the size of estimate of the domain of attraction. Significantly, the convergence of all admissible initial states within this region could be ensured. Based on the Lyapunov-Krasovskii delay-independent and delay-dependent analyses, sufficient conditions for the robust stabilization are derived. These conditions are formulated as a convex optimization problem with constraints represented by a set of linear matrix inequalities, allowing the fuzzy controller to be synthesized more efficiently. Finally, numeric simulations are given to validate the proposed approach.