北京航空航天大学学报 ›› 2015, Vol. 41 ›› Issue (1): 8-13.doi: 10.13700/j.bh.1001-5965.2014.0041

• 论文 • 上一篇    下一篇

基于Riccati方程解的高增益未知输入观测器设计

朱芳来, 张永军   

  1. 同济大学 电子与信息工程学院, 上海 200092
  • 收稿日期:2014-01-23 出版日期:2015-01-20 发布日期:2015-02-04
  • 通讯作者: 朱芳来(1965-),男,广西兴安人,教授,zhufanglai@tongji.edu.cn,主要研究方向为非线性系统鲁棒控制,基于模型的故障检测与故障重构等. E-mail:zhufanglai@tongji.edu.cn
  • 基金资助:

    国家自然科学基金资助项目(61074009);高等学校博士学科点专项科研基金资助项目(20110072110015);广西制造系统与先进制造技术重点实验室项目(PF110289);上海重点学科项目(B004)

Design of high-gain unknown input observer based on Riccati equation

ZHU Fanglai, ZHANG Yongjun   

  1. College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China
  • Received:2014-01-23 Online:2015-01-20 Published:2015-02-04

摘要:

针对具有未知输入和测量噪声的一类Lipschitz非线性系统,研究了状态估计、噪声估计及未知输入重构问题.通过将输出噪声看作扩展状态,把原系统转化为描述系统.针对描述系统,首先基于Riccati方程的解,提出了一种高增益观测器设计方法,实现对系统状态的估计和测量噪声的重构;之后,设计二阶高增益滑模观测器精确估计输出的微分,并利用状态和输出微分的估计,提出了一种未知输入的重构方法.在一Riccati方程有解的前提下,所提出的未知输入和测量噪声的重构,均适用于强时变信号.最后,对一个实际模型仿真,验证所提出方法的有效性.

关键词: 未知输入观测器, 测量噪声估计, Riccati方程, 未知输入重构, 高增益

Abstract:

For a class of Lipschitz nonlinear system, the reconstruction problems of state estimation, unknown input and measurement noise were studied. Regarding the measurement noise as an extended state, the original system can be transformed into a descriptor system. For the descriptor system, first, a high-gain observer which can estimate the states and the measurement noise of original system simultaneously was developed based on the solution of a Riccati equation. Second, a second-order high gain sliding mode observer was used to exactly estimate the derivatives of the system outputs in a finite time. Third, by using the estimates of the states and the output derivatives, an algebraic unknown input reconstruction method was proposed. It was pointed out that both the unknown input and measurement noise reconstruction methods are suitable for stronger time-varying signals. Finally, a numerical simulation of a practical model was given to illustrate the effectiveness of the proposed methods.

Key words: unknown input observer, measurement noise reconstruction, Riccati equation, unknown input reconstruction, high-gain

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