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Decentralized output feedback adaptive NN tracking control of interconnected nonlinear time-delay systems with prescribed performance

机译:具有规定性能的非线性时滞系统的分散输出反馈自适应NN跟踪控制

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This paper studies the decentralized output feedback adaptive NN tracking control problem for interconnected nonlinear time-delay systems with prescribed performance. By using the novel states transformation, the prescribed tracking performance can be guaranteed. Firstly, we design the decentralized filters independent of time delay to estimate the unmeasured state variables. By estimating the bounds of the unknown parameters instead of themselves, it can avoid the over-estimation problem. Then, by using RBF (radial basis function) neural network (NN) to approximate the unavailable time-delay functions, we construct the adaptive neural network output feedback controller with corresponding adaptive laws. It is proved that all the signals of the overall closed-loop systems are ultimately uniformly bounded. Finally, simulation examples are presented to verify the effectiveness of the theoretic results obtained. (C) 2015 Elsevier B.V. All rights reserved.
机译:研究了具有规定性能的互联非线性时滞系统的分散输出反馈自适应NN跟踪控制问题。通过使用新颖的状态变换,可以确保指定的跟踪性能。首先,我们设计了与时间延迟无关的分散滤波器,以估计未测量的状态变量。通过估计未知参数的边界而不是它们自己,可以避免过高估计的问题。然后,利用径向基函数神经网络(RBF)对不可用的时延函数进行近似,构造具有相应自适应律的自适应神经网络输出反馈控制器。事实证明,整个闭环系统的所有信号最终都是均匀有界的。最后,通过仿真实例验证了所获得理论结果的有效性。 (C)2015 Elsevier B.V.保留所有权利。

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