基于2D模型的网络系统迭代学习控制设计方法  

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

作　　者：尹艳玲[1] 王泰华[1] 曾旗[2] 

机构地区：[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　　处：《系统工程与电子技术》2015年第5期1157-1162,共6页Systems Engineering and Electronics

基　　金：国家自然科学基金(61203065);河南省控制工程重点学科开放实验室项目(KG2011-10)资助课题

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。When the iterative learning control（ILC）is applied to networked control systems, packet drop- outs 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 stochas- tic 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 de- fined 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 effective- ness of the proposed method is illustrated by a numerical example.

关 键 词：迭代学习控制 网络控制系统 数据包丢失 2D-Roesser模型 随机系统 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]