A parameter estimation perspective of continuous time model reference adaptive control
Automatica (Journal of IFAC)
Adaptive control of mechanical manipulators
Adaptive control of mechanical manipulators
Adaptive control: stability, convergence, and robustness
Adaptive control: stability, convergence, and robustness
An introduction to wavelets
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Industrial Applications of Fuzzy Control
Industrial Applications of Fuzzy Control
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators
Intelligent Control: Aspects of Fuzzy Logic and Neural Nets
Intelligent Control: Aspects of Fuzzy Logic and Neural Nets
Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximation Techniques
H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach
IEEE Transactions on Fuzzy Systems
Stable adaptive control using fuzzy systems and neural networks
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
An improved stable adaptive fuzzy control method
IEEE Transactions on Fuzzy Systems
The adaptive control of nonlinear systems using the Sugeno-type of fuzzy logic
IEEE Transactions on Fuzzy Systems
Brief Robust tracking control for nonlinear MIMO systems via fuzzy approaches
Automatica (Journal of IFAC)
Information Sciences: an International Journal
Adaptive type-2 fuzzy sliding mode controller for SISO nonlinear systems subject to actuator faults
International Journal of Automation and Computing
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This paper addresses robust fuzzy adaptive control for nonlinear multi-input multi-output systems in the presence of parametric uncertainties and external disturbances. A universal approximator is used to approximate the plant model. The boundedness of the variables involved and convergence towards zero of the tracking error are guaranteed by a supervisory control. The effect of both the approximation errors and the external disturbances is attenuated to a prescribed level via an H∞ supervisor. Sufficient conditions are derived for robust stabilization in the sense of Lyapunov asymptotic stability. The effectiveness of the proposed controller design methodology is demonstrated by numerical simulations of a two-link robot.