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Research on Adaptive Neural Network Control System Based on Nonlinear U-Model with Time-Varying Delay

机译:基于时滞非线性U模型的自适应神经网络控制系统研究

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摘要

U-model can approximate a large class of smooth nonlinear time-varying delay system to any accuracy by using time-varying delay parameters polynomial. This paper proposes a new approach, namely, U-model approach, to solving the problems of analysis and synthesis for nonlinear systems. Based on the idea of discrete-time U-model with time-varying delay, the identification algorithm of adaptive neural network is given for the nonlinear model. Then, the controller is designed by using the Newton-Raphson formula and the stability analysis is given for the closed-loop nonlinear systems. Finally, illustrative examples are given to show the validity and applicability of the obtained results.
机译:通过使用时变延迟参数多项式,U模型可以将一类光滑的非线性时变延迟系统近似为任意精度。本文提出了一种新的方法,即U模型方法,来解决非线性系统的分析和综合问题。基于具有时变时滞的离散时间U模型的思想,给出了非线性模型的自适应神经网络识别算法。然后,使用牛顿-拉夫森公式设计控制器,并给出了闭环非线性系统的稳定性分析。最后,通过举例说明了所获得结果的有效性和适用性。

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