Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Design of fuzzy control systems with guaranteed stability
Fuzzy Sets and Systems
Automatica (Journal of IFAC)
Analysis and design for a class of complex control systems part II: fuzzy controller design
Automatica (Journal of IFAC)
Stable and optimal adaptive fuzzy control of complex systems using fuzzy dynamic model
Fuzzy Sets and Systems - Theme: Fuzzy control
Stability analysis of fuzzy control systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Design of a stable fuzzy controller for an articulated vehicle
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Stability and stabilizability of fuzzy-neural-linear control systems
IEEE Transactions on Fuzzy Systems
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
A formal approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
A new approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs
IEEE Transactions on Fuzzy Systems
Stabilizing controller design for uncertain nonlinear systems using fuzzy models
IEEE Transactions on Fuzzy Systems
Analysis and design of fuzzy control systems using dynamic fuzzy-state space models
IEEE Transactions on Fuzzy Systems
Stabilizing fuzzy system models using linear controllers
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Fuzzy model based adaptive control for a class of nonlinear systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
An approach to adaptive control of fuzzy dynamic systems
IEEE Transactions on Fuzzy Systems
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In this work, we present a state feedback adaptive fuzzy control method, applied to the stabilization of a nonlinear system whose mathematical model is unknown or/and with varying time parameters. The synthesis of the control law is based on fuzzy models developed by a local description of the considered system's dynamics. Therefore, two steps, at each time, are necessary to the adaptive control of such system. The first one consists in estimating every local model parameters, using a gradient method as parameter's adjustment method. The second one consists in the computation, of the control law based on the classical methods applied for the linear system control as the state feedback control. The stability of the proposed adaptive control method is discussed.