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A B-spline neural-network-based variable structure controller (VSC) for a class of nonlinear systems with parameter uncertainties is presented. The neural networks compensator is used to compensate the uncertainties in the systems. The tracking performance and stability is guaranteed by the VSC controller. The asymptotical stability of overall systems is verified by the Lyapunov stability criterion...
A robust adaptive neural network control scheme is proposed for a class of strict-feedback nonlinear systems with unknown control directions and unmodeled dynamics. The proposed design method expands the class of nonlinear systems for which robust adaptive control approaches have been studied. A priori knowledge of the signs of the control directions is not required. It is proved that under the proposed...
This paper proposes a novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients. Based on the radial basis function neural network online approximation capability, an adaptive neural controller is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals. The proposed controller guarantees...
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