Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Robust adaptive control
Nonlinear control design: geometric, adaptive and robust
Nonlinear control design: geometric, adaptive and robust
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Stable Adaptive Neural Network Control
Stable Adaptive Neural Network Control
Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust backstepping control of nonlinear systems using neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Stable adaptive control using fuzzy systems and neural networks
IEEE Transactions on Fuzzy Systems
Adaptive fuzzy-based tracking control for nonlinear SISO systems via VSS and H∞ approaches
IEEE Transactions on Fuzzy Systems
Adaptive control of a class of nonlinear systems with nonlinearly parameterized fuzzy approximators
IEEE Transactions on Fuzzy Systems
Adaptive neural network control for strict-feedback nonlinear systems using backstepping design
Automatica (Journal of IFAC)
Neural network adaptive robust control of nonlinear systems in semi-strict feedback form
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Adaptive robust control of MIMO nonlinear systems in semi-strict feedback forms
Automatica (Journal of IFAC)
Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Stable neural controller design for unknown nonlinear systems using backstepping
IEEE Transactions on Neural Networks
Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems
IEEE Transactions on Neural Networks
Robust and adaptive backstepping control for nonlinear systems using RBF neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Adaptive backstepping fuzzy control for nonlinearly parameterized systems with periodic disturbances
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
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This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.