Identification and control of Sandwich system with backlash

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• 英文论文题名：Identification and control of Sandwich system with backlash
• 论文作者：Linwei Li ; Xuemei Ren ; Minlin Wang ; Yongfeng Lv
• 英文论文作者：Linwei Li ; Xuemei Ren ; Minlin Wang ; Yongfeng Lv ; School of Automation ; Beijing Institute of Technology
• 年：2017
• 作者机构：School of Automation,Beijing Institute of Technology;
• 英文论文关键词：Multi-innovation identification ; PID ; Sandwich system ; Backlash ; the key-term separation principle
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（A）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（A）
• 语种：英文
• 分类号：O212.1;O231
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：6
• 文件大小：1091k
• 原文格式：D
• 会议级别：全国

摘要

The identification and control of Sandwich systems are surveyed for the systems which involve backlash nonlinearity. The focus is made on the way of constructing the identification model and the convergence rate of the identification algorithm. Based on a parameterization of backlash, the Sandwich system with backlash is constructed as a regression model in which the backlash parameter and linear subsystems parameters are separated by using the key-term separation principle. In order to improve the convergence rate, a multi-innovation least squares algorithm is applied to identify the parameter of the regression equation by modifying the scalar single innovation as multi-innovation matrix. Finally, a traditional PID controller achieves a reference signal tracking based on the result of the parameter estimation.
The identification and control of Sandwich systems are surveyed for the systems which involve backlash nonlinearity. The focus is made on the way of constructing the identification model and the convergence rate of the identification algorithm. Based on a parameterization of backlash, the Sandwich system with backlash is constructed as a regression model in which the backlash parameter and linear subsystems parameters are separated by using the key-term separation principle. In order to improve the convergence rate, a multi-innovation least squares algorithm is applied to identify the parameter of the regression equation by modifying the scalar single innovation as multi-innovation matrix. Finally, a traditional PID controller achieves a reference signal tracking based on the result of the parameter estimation.

引文

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