Observer-based adaptive iterative learning control for nonlinear systems with time-varying delays
Observer-based adaptive iterative learning control for nonlinear systems with time-varying delays
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DOI：
10.1007/s11633-010-0525-5
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发表时间：
2010-11
影响因子：
4.3
通讯作者：
Weisheng Chen;Rui-hong Li;Jing Li
中科院分区：
文献类型：
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作者：
Weisheng Chen;Rui-hong Li;Jing Li
针对一类具有未知时变参数和未知时变时滞的非线性系统，提出了一种基于模糊控制器的自适应迭代学习控制（AILC）方法。采用线性矩阵不等式（LMI）方法设计非线性观测器。所设计的控制器包含一个比例积分微分（PID）反馈项在时域。对未知常参数的学习规律为微分-差分型，对未知时变参数的学习规律为差分型。假设未知的时滞相关不确定性是非线性参数化的。通过构造类Lyapunov-Krasovskii复合能量函数（CEF），证明了所有闭环信号的有界性和跟踪误差的收敛性。最后给出了一个仿真例子来说明本文所提出的控制算法的有效性。
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.