H∞ tracking of uncertain SISO nonlinear systems: an observer-based adaptive fuzzy approach
International Journal of Systems Science
Adaptive fuzzy control for uncertain interconnected time-delay systems
Fuzzy Sets and Systems
Adaptive fuzzy control of a class of decentralized nonlinear systems and unknown dynamics
Control and Intelligent Systems
Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Information Sciences: an International Journal
Interval type 2 hierarchical FNN with the H-infinity condition for MIMO non-affine systems
Applied Soft Computing
Adaptive control for nonlinear MIMO time-delay systems based on fuzzy approximation
Information Sciences: an International Journal
Control of an Industrial PA10-7CE Robot Arm Based on Decentralized Neural Backstepping Approach
Neural Processing Letters
Hybrid-fuzzy modeling and identification
Applied Soft Computing
Adaptive fuzzy control for differentially flat MIMO nonlinear dynamical systems
Integrated Computer-Aided Engineering
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In this paper, direct and indirect adaptive output-feedback fuzzy decentralized controllers for a class of uncertain large-scale nonlinear systems are developed. The proposed controllers do not need the availability of the state variables. By designing the state observer, the adaptive fuzzy systems, which are used to model the unknown functions, can be constructed using the state estimations, and a new hybrid adaptive fuzzy control methodology is proposed by combining the adaptive fuzzy systems with H∞ control and the sliding mode control techniques. Based on Lyapunov stability theorem, the stability of the closed-loop systems can be verified. Moreover, the proposed overall control schemes guarantee that all the signals involved are bounded and achieve the H∞-tracking performance. To demonstrate the effectiveness of the proposed methods, simulation results are illustrated in this paper.