基于2D模型的网络系统迭代学习控制设计方法

系统工程与电子技术

基于2D模型的网络系统迭代学习控制设计方法

尹艳玲1, 王泰华1, 曾旗2

(1. 河南理工大学电气工程与自动化学院, 河南焦作 454000;
2. 河南理工大学经济管理学院, 河南焦作 454003)

出版日期:2015-04-23 发布日期:2010-01-03

Networkbased iterative learning control design based on 2D model

YIN Yanling1, WANG Taihua1, ZENG Qi2

(1. School of Electrical Engineering & Automation, Henan Polytechnic University, Jiaozuo 454000, China;2. School of Economics and Management, Henan Polytechnic University, Jiaozuo 454003, China)

Online:2015-04-23 Published:2010-01-03

摘要/Abstract

摘要：

迭代学习控制(iterative learning control, ILC)方法应用于网络控制系统时,由于数据需要在控制器和远程对象间传输经常产生数据丢失现象。给出了一种存在数据丢失时网络系统的随机迭代学习控制设计方法,首先将数据丢失现象描述为随机伯努利序列,在此基础上将迭代学习的控制器设计转化为随机〖JP2〗2DRoesser系统的稳定问题。定义了随机意义下2D系统的均方渐进稳定,基于线性矩阵不等式(linear matrix inequality, LMI)给出一个判别稳定性的条件,该条件同时可实现迭代学习控制器的设计。仿真示例验证了设计方法的有效性。

Abstract:

When the iterative learning control(ILC)is applied to networked control systems, packet dropouts often occur due to the data transfer from the remote plant to the ILC controller. A stochastic ILC design approach for networked control systems with data dropouts is given. Missing data is firstly modeled by stochastic variables satisfying the Bernoulli random binary distribution. Then, the design of ILC is transformed into the stability of a 2D stochastic system described by the Roesser model. The meansquare asymptotic stability is defined for such 2D stochastic systems. A sufficient condition for stability is established by means of linear matrix inequality(LMI)technique, and formulas can be given for the controller design simultaneously. The effectiveness of the proposed method is illustrated by a numerical example.

尹艳玲1, 王泰华1, 曾旗2. 基于2D模型的网络系统迭代学习控制设计方法[J]. 系统工程与电子技术.

YIN Yanling1, WANG Taihua1, ZENG Qi2. Networkbased iterative learning control design based on 2D model[J]. Systems Engineering and Electronics.