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Adaptive neural control for a class of nonlinearly parametric time-delay systems

机译:一类非线性参数时滞系统的自适应神经控制

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In this paper, an adaptive neural controller for a class of time-delay nonlinear systems with unknown nonlinearities is proposed. Based on a wavelet neural network (WNN) online approximation model, a state feedback adaptive controller is obtained by constructing a novel integral-type Lyapunov-Krasovskii functional, which also efficiently overcomes the controller singularity problem. It is shown that the proposed method guarantees the semiglobal boundedness of all signals in the adaptive closed-loop systems. An example is provided to illustrate the application of the approach.
机译:针对非线性未知的一类时滞非线性系统,提出了一种自适应神经控制器。基于小波神经网络在线逼近模型,通过构造新型积分型Lyapunov-Krasovskii泛函获得状态反馈自适应控制器,有效地克服了控制器的奇异性问题。结果表明,该方法可以保证自适应闭环系统中所有信号的半全局有界性。提供了一个示例来说明该方法的应用。

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