Nonlinear state feedback for l1 optimal control
Systems & Control Letters
Control of uncertain systems: a linear programming approach
Control of uncertain systems: a linear programming approach
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Design of output feedback controllers for Takagi—Sugeno fuzzy systems
Fuzzy Sets and Systems - Special issue on formal methods for fuzzy modeling and control
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Conditions of output stabilization for nonlinear models in the Takagi--Sugeno's form
Fuzzy Sets and Systems
Dynamic output feedback controller design for fuzzy systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust H∞ static output feedback control of fuzzy systems: an ILMI approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs
IEEE Transactions on Fuzzy Systems
Discrete-time optimal fuzzy controller design: global concept approach
IEEE Transactions on Fuzzy Systems
On relaxed LMI-based designs for fuzzy regulators and fuzzy observers
IEEE Transactions on Fuzzy Systems
New fuzzy control model and dynamic output feedback parallel distributed compensation
IEEE Transactions on Fuzzy Systems
The fuzzy discrete-time robust regulation problem: an LMI approach
IEEE Transactions on Fuzzy Systems
Robust H∞ control for uncertain discrete-time-delay fuzzy systems via output feedback controllers
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Output Feedback Control of Discrete-Time Fuzzy Systems With Application to Chaos Control
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Systems with persistent disturbances: predictive control with restricted constraints
Automatica (Journal of IFAC)
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)
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To date, nonlinear l∞-gain control problems have not been solved by the conventional control methods for nonlinear discrete-time systems with persistent bounded disturbances. This study introduces fuzzy observer-based fuzzy control design, where the premise variables depend on the state variables estimated by a fuzzy observer, to deal with the nonlinear l∞-gain control problem. The fuzzy control design for this case is more flexible but much more complex than that for the case where the premise variables depend on the state variables. First, the Takagi-Sugeno (T-S) fuzzy model is employed to represent the nonlinear discrete-time system. Next, based on the fuzzy model, a fuzzy observer-based fuzzy controller is developed to minimize the upper bound of l∞-gain of the closed-loop system under some nonlinear matrix inequality (non-LMI) constraints. A novel decoupled method is proposed in this study to transform the non-LMI conditions into some linear matrix inequality (LMI) forms. By the proposed decoupled method and the genetic algorithm, the l∞-gain fuzzy observer-based fuzzy control problem for the nonlinear discrete-time systems can be easily solved by an LMI-based optimization method. The proposed methods, which efficiently attenuate the peak of perturbation due to persistent bounded disturbances, extend the l∞-gain control problems from linear discrete-time systems to nonlinear discrete-time systems. A simulation example is given to illustrate the design procedures and to confirm the l∞-gain performance of the proposed method.