Adaptive NN Control for a Class of Strict-Feedback Discrete-Time Nonlinear Systems with Input Saturation

In this paper, an adaptive neural network (NN) control scheme is proposed for a class of strict-feedback discrete-time nonlinear systems with input saturation. which is designed via backstepping technology and the approximation property of the HONNs, aimed to solve the the input saturation constraint and system uncertainty in many practical applications. The closedloop system is proven to be uniformly ultimately bounded (UUB). At last, a simulation example is given to illustrate the effectiveness of the proposed algorithm.

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