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同时含有未知输入和测量干扰系统全维和降维观测器设计

吴阳 张建成

吴阳, 张建成. 同时含有未知输入和测量干扰系统全维和降维观测器设计. 自动化学报, 2022, 48(8): 2108−2118 doi: 10.16383/j.aas.c190505
引用本文: 吴阳, 张建成. 同时含有未知输入和测量干扰系统全维和降维观测器设计. 自动化学报, 2022, 48(8): 2108−2118 doi: 10.16383/j.aas.c190505
Wu Yang, Zhang Jian-Cheng. Full- and reduced-order observer design for systems with both the unknown inputs and measurement disturbances. Acta Automatica Sinica, 2022, 48(8): 2108−2118 doi: 10.16383/j.aas.c190505
Citation: Wu Yang, Zhang Jian-Cheng. Full- and reduced-order observer design for systems with both the unknown inputs and measurement disturbances. Acta Automatica Sinica, 2022, 48(8): 2108−2118 doi: 10.16383/j.aas.c190505

同时含有未知输入和测量干扰系统全维和降维观测器设计

doi: 10.16383/j.aas.c190505
基金项目: 国家自然科学基金(61803181), 中国博士后科学基金(2019M651695), 江苏高校“青蓝工程” 优秀青年骨干教师项目基金 (苏教师函 [2021] 11)资助
详细信息
    作者简介:

    吴阳:无锡太湖学院智能装备工程学院副教授. 主要研究方向为故障检测与估计, 智能控制, 系统优化. E-mail: wuy1@wxu.edu.cn

    张建成:江南大学理学院副教授. 2017年获得同济大学控制科学与工程系博士学位. 主要研究方向为有限时间观测器设计, 故障检测与估计, 滑模控制. 本文通信作者. E-mail: jcz@jiangnan.edu.cn

Full- and Reduced-order Observer Design for Systems With Both the Unknown Inputs and Measurement Disturbances

Funds: Supported by National Natural Science Foundation of China (61803181), China Postdoctoral Science Foundation (2019M651695), and Outstanding Young Backbone Teacher Project of Jiangsu University “Qinglan Project” (Su Teacher [2021] No. 11)
More Information
    Author Bio:

    WU Yang Associate professor at the School of Intelligent Equipment Engineering, Wuxi Taihu University. His research interest covers fault detection and estimation, intelligent control, and system optimization

    ZHANG Jian-Cheng Associate professor at the School of Science, Jiangnan University. He received his Ph.D. degree in control theory and control engineering from Tongji University in 2017. His research interest covers finite-time observer design, fault detection and fault estimation, and sliding mode control. Corresponding author of this paper

  • 摘要: 针对同时含有未知输入和测量干扰的不确定系统研究了全维和降维观测器设计问题. 首先, 利用待定系数法给出了全维观测器的结构和存在条件. 该条件完全由原系统的系统矩阵给出, 易于检验. 对于降维观测器, 为了消除测量干扰的影响, 提出了一种新的测量输出构造方法, 使得新构造的测量输出不再包含干扰信号. 此外, 证明了全维和降维观测器存在条件的内在统一性, 即全维观测器所需要满足的观测器匹配条件和强可检测条件在研究降维观测器所要讨论的新的系统中都可以得到保持. 因而, 在全维观测器存在条件下, 也可以设计一个相应的降维观测器. 最后, 给出了一个数值例子验证所提方法的有效性.
  • 图  1  系统状态及其估计(全维观测器)

    Fig.  1  Actual states and their estimations (full-order observer)

    图  2  系统状态及其估计(降维观测器)

    Fig.  2  Actual states and their estimations (reduced-order observer)

    图  3  方波形未知输入信号

    Fig.  3  Square wave unknown input signal

    图  4  锯齿形测量干扰信号

    Fig.  4  Sawtooth measurement disturbance signal

    图  5  方波和锯齿干扰信号下的状态估计

    Fig.  5  State estimations under square wave and sawtooth disturbance signals

    图  6  在受到噪声信号1影响下的状态估计

    Fig.  6  State estimations under the influence of noise signal (Type l)

    图  7  在受到噪声信号2影响下的状态估计

    Fig.  7  State estimations under the influence of noise signal (Type 2)

    图  8  在受到噪声信号3影响下的状态估计

    Fig.  8  State estimations under the influence of noise signal (Type 3)

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出版历程
  • 收稿日期:  2019-07-02
  • 录用日期:  2019-10-21
  • 网络出版日期:  2022-07-07
  • 刊出日期:  2022-06-01

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