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Adaptive neural network tracking control for a class of unknown nonlinear time-delay systems

机译:一类未知非线性时滞系统的自适应神经网络跟踪控制

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摘要

For a class of unknown nonlinear time-delay systems, an adaptive neural network (NN) control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a robust memoryless adaptive NN tracking controller. Unknown time-delay functions are approximated by NNs, such that the requirement on the nonlinear time-delay functions is relaxed. Based on Lyapunov-Krasoviskii functional, the sem-global uniformly ultimately boundedness (UUB) of all the signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.
机译:针对一类未知的非线性时滞系统,提出了一种自适应神经网络控制设计方法。将反推,控制和自适应边界设计技术相结合,构建了一种健壮的无记忆自适应神经网络跟踪控制器。未知的时延函数由NN逼近,从而放松了对非线性时延函数的要求。基于Lyapunov-Krasoviskii泛函,证明了闭环系统中所有信号的sem-global统一最终有界性(UUB)。通过调整设计参数可以实现任意输出跟踪精度。通过说明性的仿真示例研究了可行性。

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