东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2013, Vol. 34 ›› Issue (7): 913-916.DOI: -

• 信息与控制 •    下一篇

离散化采样控制系统的故障估计

李宁，冯健   

  1. (东北大学信息科学与工程学院，辽宁沈阳110819)
  • 收稿日期:2013-01-10 修回日期:2013-01-10 出版日期:2013-07-15 发布日期:2013-12-31
  • 通讯作者: 李宁
  • 作者简介:李宁(1987-)，女，河北保定人，东北大学博士研究生；冯健(1971-)，男，辽宁锦州人，东北大学教授，博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(61273164，61034005)；国家高技术研究发展计划项目(2012AA040104)；中央高校基本科研业务费专项资金资助项目(N100104102，N120504002).

Fault Estimation for Sampling Control System with Discretion

LI Ning， FENG Jian   

  1. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2013-01-10 Revised:2013-01-10 Online:2013-07-15 Published:2013-12-31
  • Contact: LI Ning
  • About author:-
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摘要： 针对一类具有采样周期一定的线性时不变采样控制系统，先给出系统范数的定义，然后利用自定义的系统范数对系统同时进行范数不变变形离散化和阶跃不变变形离散化，得到系统的离散形式模型.考虑H_/H∞，H2/H∞和H∞/H∞故障检测问题，给出离散系统的最优滤波器的形式；基于该离散系统的最优滤波器的设计思想和设计方法，给出系统的故障估计观测器设计方法和设计形式，构造Lyapunov函数得到误差方程渐近稳定的必要条件，通过MatlabLMI工具箱得到故障估计自适应权重矩阵Γ和参数θ.最后通过数值算例证明了该方法的有效性.

关键词: 范数不变, 阶跃不变, 采样系统, 故障检测, 故障估计

Abstract: To study a class of linear time invariant sampling control system with periodic sample， the following steps were carried out. Firstly， the definition of system norm was given， and then the system was dispersed simultaneously by norm invariant transformation and step invariant transformation based on the definition of system norm to get the discretion model of the system. Secondly， fault detection problems of H_/H∞， H2/H∞ and H∞/H∞ were considered， and the form of the optimal filter was provided. At the same time， based on the design idea and method of the optimal filter for discrete system， the design method and form of the fault estimation observer were given out， and the essential condition of the error equation asymptotic stability was gotten by structuring Lyapunov function. What’s more， the fault estimation adaptive weighting matrix Γ and parameter θ were solved by Matlab LMI toolbox as well. At last， a numerical example was given to illustrate the effectiveness of the proposed method.

Key words: norm invariant, step invariant, sampling system, fault detection, fault estimation

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