Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems
Automatica (Journal of IFAC)
Adaptive fuzzy control of MIMO nonlinear systems
Fuzzy Sets and Systems
Stable adaptive fuzzy sliding mode control of interconnected systems
Fuzzy Sets and Systems
Information Sciences—Informatics and Computer Science: An International Journal
Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping approach
Fuzzy Sets and Systems
Automatica (Journal of IFAC)
Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems
Information Sciences: an International Journal
Observer-based adaptive control of robot manipulators: Fuzzy systems approach
Applied Soft Computing
Adaptive fuzzy output tracking control for a class of uncertain nonlinear systems
Fuzzy Sets and Systems
Fuzzy adaptive observer backstepping control for MIMO nonlinear systems
Fuzzy Sets and Systems
Direct adaptive self-structuring fuzzy controller for nonaffine nonlinear system
Fuzzy Sets and Systems
Observer-based adaptive fuzzy-neural control for unknown nonlineardynamical systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive fuzzy decentralized control fora class of large-scale nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive robust fuzzy control of nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive Neural Control for a Class of Perturbed Strict-Feedback Nonlinear Time-Delay Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Fuzzy Systems
Two-Mode Adaptive Fuzzy Control With Approximation Error Estimator
IEEE Transactions on Fuzzy Systems
Stable adaptive fuzzy control of nonlinear systems
IEEE Transactions on Fuzzy Systems
Brief Robust tracking control for nonlinear MIMO systems via fuzzy approaches
Automatica (Journal of IFAC)
Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems
IEEE Transactions on Neural Networks
Nonlinear adaptive control of interconnected systems using neural networks
IEEE Transactions on Neural Networks
A hierarchical structure of observer-based adaptive fuzzy-neural controller for MIMO systems
Fuzzy Sets and Systems
Interval type 2 hierarchical FNN with the H-infinity condition for MIMO non-affine systems
Applied Soft Computing
Universal fuzzy controllers based on generalized T--S fuzzy models
Fuzzy Sets and Systems
Adaptive fuzzy tracking control of nonlinear MIMO systems with time-varying delays
Fuzzy Sets and Systems
Stability analysis and design of a class of MIMO fuzzy control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Robust PID TS fuzzy control methodology based on gain and phase margins specifications
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper addresses the adaptive fuzzy tracking control problem for a class of uncertain nonlinear MIMO systems with the external disturbances. The adaptive fuzzy controllers are designed under the constraint that only system output is available for measurement. Then, it is needed to design a state observer to estimate the unmeasured states. In the observer design procedure, two prominent advantages are that it does not require the sign of the control gain coefficient to be known and only two parameters need to be adjusted on-line for each subsystem. By using Lyapunov analysis method, it is proven that all the signals in the closed-loop system are guaranteed to be bounded and the system outputs track the reference signals to a bounded compact set. The feasibility of the proposed approach is validated by using two simulation examples.