| 引用本文: | 李昇平.l1鲁棒辨识: 最小二乘算法及试验设计[J].控制理论与应用,2003,20(4):492~496.[点击复制] |
| LI Sheng-ping.l1 robust identification: least squares algorithm and experimental design[J].Control Theory and Technology,2003,20(4):492~496.[点击复制] |
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| l1鲁棒辨识: 最小二乘算法及试验设计 |
| l1 robust identification: least squares algorithm and experimental design |
| 摘要点击 2024 全文点击 1183 投稿时间：2001-05-28 修订日期：2002-11-15 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.4.002 |
| 2003,20(4):492-496 |
| 中文关键词 l1鲁棒辨识 最小二乘法 时变系统 试验设计 |
| 英文关键词 l1 robust identification least squares algorithm time varying system experimental design |
| 基金项目 广东省自然科学基金(990795); 国家计委“工业自动化关键技术研制开发及产业化”子课题; 汕头大学研究与发展基金 |
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| 中文摘要 |
| 现有的l1鲁棒辨识方法依赖于观测数据自的起始时刻因而不能用来辨识时变系统, 针对该问题基于最小二乘法提出了一种l1鲁棒辨识算法. 该算法与观测窗的起始时刻无关, 可用于时变系统的辨识, 证明了当试验输入为持续激励信号时所提出的算法为本质最优算法, 进一步证明了周期持续激励序列为最优试验信号, 并给出了辨识误差紧界的计算公式. 最后利用提出的算法研究了慢时变系统的l1鲁棒辨识问题. |
| 英文摘要 |
| Based on least squares algorithm a new l1 robust identifying approach was proposed, which was independent of the starting time of observation windows, and therefore, could be used to identify the time varying system. It was shown that the proposed algorithm was essentially optimal when the experimental input was selected as a persistent signal. Furthermore, the periodic persistent signal was proved to be the optimal experimental signal. Finally, the proposed algorithm was applied to slowly varying system. |