Structure identification of fuzzy model
Fuzzy Sets and Systems
A course in fuzzy systems and control
A course in fuzzy systems and control
Linear System Theory and Design
Linear System Theory and Design
Information Sciences—Informatics and Computer Science: An International Journal
Robust adaptive fuzzy controller for nonlinear system with unknown nonlinearities
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Stability analysis and design of Takagi-Sugeno fuzzy systems
Information Sciences: an International Journal
Stable adaptive fuzzy controllers with application to inverted pendulum tracking
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive neural network control of nonlinear systems by state andoutput feedback
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fuzzy disturbance observer and its application to control
IEEE Transactions on Fuzzy Systems
Dynamic structure neural networks for stable adaptive control of nonlinear systems
IEEE Transactions on Neural Networks
New results on H∞ filtering for fuzzy systems with interval time-varying delays
Information Sciences: an International Journal
Information Sciences: an International Journal
Adaptive control for nonlinear MIMO time-delay systems based on fuzzy approximation
Information Sciences: an International Journal
Fuzzy modeling approach to predictions of chemical oxygen demand in activated sludge processes
Information Sciences: an International Journal
Relaxed stability issues for T-S fuzzy system: Based on a fuzzy quadratic Lyapunov function
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper proposes the design scheme of the alternative adaptive observer and controller based on the Takagi-Sugeno (T-S) fuzzy model. The T-S fuzzy modeling and the state feedback control technique are adopted for the simple structure. The proposed method maintains consistent performance in the presence of parameter uncertainties and incorporates linguistic fuzzy information from human operators. In addition, with the simple adaptive state feedback controller, it solves the singularity problem, which occurs in the inverse dynamics based on the feedback linearization method. Using Lyapunov theory and Lipschitz condition, the stability analysis is conducted, and the adaptive law is derived. The proposed method is applied to the stabilization problem of a flexible joint manipulator in order to guarantee its performance.