Adaptive Learning Control for Nonparametric Systems with Bouc-Wen Hysteresis Input

In this paper, an adaptive iterative learning control scheme is propsed for a class of nonparametric systems with hysteresis input described by Bouc-Wen model. First, based on analyzing the property of Bouc-Wen model, the adaptive learning controller is designed by using Lyapunov synthesis. In the control design, the nonparametric uncertainty and hysteresis nonlinearity is compensated by robust strategy and iterative learning strategy together, according to the property of Bouc-Wen model. As the iteration increases, the system state can track its reference signal accurately over the whole period. Numerical results demonstrate the effectiveness of the adaptive learning control scheme.

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