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The problem of robust fuzzy control for a class of nonlinear systems subject to impulsive disturbance of input is investigated by employing Lyapunov functions in this paper. The well-known T-S fuzzy model is used to represent the nonlinear systems. The so-called parallel distributed compensation (PDC) idea is employed to design the state feedback controller. Two classes of coefficient matrices of...
The paper investigates the adaptive neural network control design for a class of nonlinear systems with input nonlinearity using Lyapunov's stability theory. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks (MNNs), a novel sliding mode neural network control strategy with supervisory controller is developed. With the help of a supervisory...
The problem of adaptive fuzzy sliding mode control for a class of nonlinear systems with unknown virtual control coefficients and perturbed uncertainties is discussed in this paper. By introducing boundary layer, and combining backstepping technique with direct adaptive control, a novel scheme of adaptive fuzzy control is proposed. In order to reduce the modeling error effect and improve the control...
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