| 引用本文: | 杨志刚, 曹长修, 苏玉刚.最佳动力换档规律自学习算法的收敛性分析[J].控制理论与应用,2003,20(1):33~36.[点击复制] |
| YANG Zhi-gang, CAO Chang-xiu, SU Yu-gang.Convergence analysis of self-learning algorithm for optimal power shift schedule[J].Control Theory and Technology,2003,20(1):33~36.[点击复制] |
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| 最佳动力换档规律自学习算法的收敛性分析 |
| Convergence analysis of self-learning algorithm for optimal power shift schedule |
| 摘要点击 1664 全文点击 1354 投稿时间：2001-11-01 修订日期：2002-04-08 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.1.007 |
| 2003,20(1):33-36 |
| 中文关键词 自学习算法 收敛性 汽车AMT 最佳动力换档规律 |
| 英文关键词 self-learning algorithm convergence automobile AMT optimal shift power schedule |
| 基金项目 国家教育部博士点基金(97061104)资助项目 |
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| 中文摘要 |
| 针对汽车电控机械自动变速器 (AMT)最佳动力性换档规律的获取方法工作量大且耗资多,所得换档规律对其它车辆适应性差等问题,根据迭代自学习控制理论,提出了一种在线、实时寻求最佳动力性换档规律的自学习算法,并从理论上证明了该算法的收敛性,给出了收敛条件,讨论了自学习算法的快速收敛问题.分析结果表明,此法可以应用于实际AMT系统. |
| 英文摘要 |
| A large amount of work and money is needed to establish an optimal power shift schedule for the automated mechanical transmission (AMT) of automobile, and the existing schedule does not adapt to other types of vehicles. To solve these problems, a real-time self-learning algorithm to set up the optimal power shift schedule on line is presented on the basis of the iterative learning control theory. The convergence of the algorithm is proved, the convergence condition developed and the convergence rate also analyzed. The results of the analysis show that the algorithm can be applied to the AMT system. |
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