Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Nonlinear Control Systems II
Direct adaptive fuzzy output tracking control of nonlinear systems
Fuzzy Sets and Systems - Featured Issue: Selected papers from ACIDCA 2000
Adaptive Control Design and Analysis (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
Adaptive fuzzy control of a class of SISO nonaffine nonlinear systems
Fuzzy Sets and Systems
Stable indirect adaptive control based on discrete-time T--S fuzzy model
Fuzzy Sets and Systems
Conditions of output stabilization for nonlinear models in the Takagi--Sugeno's form
Fuzzy Sets and Systems
Constrained infinite-horizon model predictive control for fuzzy-discrete-time systems
IEEE Transactions on Fuzzy Systems
Analysis and Synthesis of Fuzzy Control Systems: A Model-Based Approach
Analysis and Synthesis of Fuzzy Control Systems: A Model-Based Approach
Stability analysis and design of Takagi-Sugeno fuzzy systems
Information Sciences: an International Journal
T-S model based indirect adaptive fuzzy control using online parameter estimation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An improved stability criterion for T-S fuzzy discrete systems via vertex expression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy model reference adaptive control
IEEE Transactions on Fuzzy Systems
Sufficient conditions for the stability of linear Takagi-Sugeno free fuzzy systems
IEEE Transactions on Fuzzy Systems
Stable auto-tuning of adaptive fuzzy/neural controllers for nonlinear discrete-time systems
IEEE Transactions on Fuzzy Systems
Adaptive Control of a Class of Nonlinear Pure-Feedback Systems Using Fuzzy Backstepping Approach
IEEE Transactions on Fuzzy Systems
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This paper develops a new solution framework for adaptive control of general discrete-time single-input single-output (SISO) state-space Takagi-Sugeno (T-S) fuzzy systems with a relative degree @r (1@?@r@?n). A new procedure is proposed to construct a normal form of a global T-S fuzzy system model from local state-space models in non-canonical form, and such a normal form system has an explicit relative degree structure and a specific input-output signal causality relationship in the sense that it does not include any future values of fuzzy membership functions. An adaptive feedback control scheme is designed based on the global normal form T-S fuzzy model, to ensure desired closed-loop stability and output tracking properties. A comparison is given to adaptive state tracking designs seen in the literature, which require much more restrictive matching conditions and do not take into account the high relative degree cases. As an illustrative example, a T-S fuzzy system is constructed based on the linearized local models of a transport airplane. Simulation results have demonstrated the developed new concepts and verified the desired performance of the new type of adaptive fuzzy control systems.