| 引用本文: | 卜旭辉,余发山,侯忠生,王福忠.测量数据丢失的一类非线性系统迭代学习控制[J].控制理论与应用,2012,29(11):1458~1464.[点击复制] |
| BU Xu-hui,YU Fa-shan,HOU Zhong-sheng,WANG Fu-zhong.Iterative learning control for a class of nonlinear systems with measurement dropouts[J].Control Theory and Technology,2012,29(11):1458~1464.[点击复制] |
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| 测量数据丢失的一类非线性系统迭代学习控制 |
| Iterative learning control for a class of nonlinear systems with measurement dropouts |
| 摘要点击 2134 全文点击 1624 投稿时间：2012-03-15 修订日期：2012-06-08 |
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| DOI编号 10.7641/j.issn.1000-8152.2012.11.CCTA120226 |
| 2012,29(11):1458-1464 |
| 中文关键词 迭代学习控制 非线性系统 网络控制系统 数据丢失 |
| 英文关键词 iterative learning control nonlinear system networked control systems data dropouts |
| 基金项目 国家自然科学基金资助项目(61203065, 60834001, 61120106009); 河南省教育厅自然科学研究计划资助项目(12A510013); 河南省高等学校控制工程重点学科开放实验室资助项目(KG2011-10). |
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| 中文摘要 |
| 迭代学习控制方法应用于网络控制系统时, 由于通信网络的约束导致数据包丢失现象经常发生. 针对存在输出测量数据丢失的一类非线性系统, 研究P型迭代学习控制算法的收敛性问题. 将数据丢失描述为一个概率已知的随机伯努利过程, 在此基础上给出P型迭代学习控制算法的收敛条件, 理论上证明了算法的收敛性, 并通过仿真验证理论结果. 研究表明, 当非线性系统存在输出测量数据丢失时, 迭代学习控制算法仍然可以保证跟踪误差的收敛性. |
| 英文摘要 |
| This paper analyzes the stability of the iterative learning control (ILC) applied to a class of nonlinear discretetime systems with output measurement data dropouts. It is assumed that an ILC scheme is implemented via a networked control loop for the nonlinear system and that the packet dropout occurs due to limitations in network communication. The data dropout is described as a stochastic Bernoulli process with a given probability; on this basis we derive the convergence condition for the P-type ILC algorithm. The theoretical analysis is supported by the simulation of a numerical example; the convergence of ILC can be guaranteed when some output measurements are missing. |