Neural network controller design for a class of nonlinear systems with unknown time delays

Shurong Li, Yun Hong
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Abstract

In this paper, an adaptive neural network controller was presented for a class of strict-feedback nonlinear systems with unknown time delays and input saturation. Based on the backstepping design technique, an adaptive controller was obtained by constructing an appropriate Lyapunov-Krasovskii functional. The saturation characteristic of the actuator was compensated by a compensator. It is proven that the semi-global uniformly ultimately boundedness of all the signals in the closed-loop systems was guaranteed. A simulation example was provided to illustrate the validity of the proposed approach.
一类未知时滞非线性系统的神经网络控制器设计
针对一类具有未知时滞和输入饱和的严格反馈非线性系统,提出了一种自适应神经网络控制器。基于反步设计技术,构造合适的Lyapunov-Krasovskii泛函,得到自适应控制器。采用补偿器补偿驱动器的饱和特性。证明了闭环系统中所有信号的半全局一致最终有界性得到了保证。仿真算例验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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