.png){kind=icon}
返回
Iterative learning control for spatially interconnected systems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.amc.2014.03.123.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Iterative learning control (ILC) has been successfully employed for trajectory tracking of uncertain dynamic systems with less system information. This paper attempts to adopt the benefits of ILC to improve the trajectory tracking performance of spatially interconnected systems. By utilizing the ILC update law along the iteration domain repetitively, a perfect reference trajectory tracking can be ensured. It is the key benefit of using ILC that less system model information is used in the design of a trajectory tracking controller for spatially interconnected systems. Through a numerical simulation, the validity of the proposed control scheme is illustrated. (C) 2014 Elsevier Inc. All rights reserved.
Keyword:
Iterative learning control
Spatially interconnected systems
Trajectory tracking
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
机构
引用论文
.png){kind=icon}
查看更多内容