Iterative Learning Control for Multiple Point-to-Point Tracking Application
Iterative Learning Control for Multiple Point-to-Point Tracking Application
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DOI：
10.1109/tcst.2010.2051670
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发表时间：
2011-05
影响因子：
4.8
通讯作者：
C. Freeman;Zhonglun Cai;E. Rogers;P. Lewin
中科院分区：
文献类型：
--
作者：
C. Freeman;Zhonglun Cai;E. Rogers;P. Lewin
本文研究了一类线性迭代学习控制算法，该算法适用于要求被控对象输出在预定时刻到达给定点的跟踪任务，且不需要指定干预参考点。一个框架是在频域中的参考试验之间更新。它示出了上级收敛性和鲁棒性与使用ILC算法的原始类跟踪指定的任意参考轨迹满足点到点的输出约束相关联的性能相比。使用非最小相位测试设备的实验结果来说明理论研究结果。
This paper considers a general class of linear iterative learning control (ILC) algorithm applied to tracking tasks which require the plant output to reach given points at predetermined time instants, without the specification of intervening reference points. A framework is developed in the frequency-domain in which the reference is updated between trials. It is shown that superior convergence and robustness properties are obtained compared with those associated with using the original class of ILC algorithm to track a prescribed arbitrary reference trajectory satisfying the point-to-point output constraints. Experimental results using a non-minimum phase test facility are presented to illustrate the theoretical findings.