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Observer-based Adaptive Iterative Learning Control for Nonlinear Systems with Time-varying Delays

机译:时变时滞非线性系统基于观测器的自适应迭代学习控制

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摘要

An observer-based adaptive iterative learning control (AILC) scheme is developed for a class of nonlinear systems with unknown time-varying parameters and unknown time-varying delays. The linear matrix inequality (LMI) method is employed to design the nonlinear observer. The designed controller contains a proportional-integral-derivative (PID) feedback term in time domain. The learning law of unknown constant parameter is differential-difference-type, and the learning law of unknown time-varying parameter is difference-type. It is assumed that the unknown delay-dependent uncertainty is nonlinearly parameterized. By constructing a Lyapunov-Krasovskii-like composite energy function (CEF), we prove the boundedness of all closed-loop signals and the convergence of tracking error. A simulation example is provided to illustrate the effectiveness of the control algorithm proposed in this paper.
机译:针对一类具有未知时变参数和未知时变延迟的非线性系统,开发了一种基于观察者的自适应迭代学习控制(AILC)方案。采用线性矩阵不等式(LMI)方法设计非线性观测器。设计的控制器在时域中包含比例积分微分(PID)反馈项。未知常数参数的学习规律为微分差分型,未知时变参数的学习规律为差分型。假定未知延迟相关不确定性是非线性参数化的。通过构造一个像Lyapunov-Krasovskii的复合能量函数(CEF),我们证明了所有闭环信号的有界性和跟踪误差的收敛性。仿真例子说明了本文提出的控制算法的有效性。

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