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基于高阶观测器和干扰补偿控制的模型预测控制方法

王东委 富月

王东委, 富月. 基于高阶观测器和干扰补偿控制的模型预测控制方法. 自动化学报, 2020, 46(6): 1220−1228 doi: 10.16383/j.aas.c180697
引用本文: 王东委, 富月. 基于高阶观测器和干扰补偿控制的模型预测控制方法. 自动化学报, 2020, 46(6): 1220−1228 doi: 10.16383/j.aas.c180697
Wang Dong-Wei, Fu Yue. Model predict control method based on higher-order observer and disturbance compensation control. Acta Automatica Sinica, 2020, 46(6): 1220−1228 doi: 10.16383/j.aas.c180697
Citation: Wang Dong-Wei, Fu Yue. Model predict control method based on higher-order observer and disturbance compensation control. Acta Automatica Sinica, 2020, 46(6): 1220−1228 doi: 10.16383/j.aas.c180697

基于高阶观测器和干扰补偿控制的模型预测控制方法

doi: 10.16383/j.aas.c180697
基金项目: 国家自然科学基金(61991403, 61991400, 61573090), 高校基本科研业务费基金(N160801001)资助
详细信息
    作者简介:

    王东委:东北大学信息科学与工程学院硕士研究生. 2016年获得郑州航空工业管理学院学士学位. 主要研究方向为自适应控制, 解耦控制. E-mail: wdw_bluesky@163.com

    富月:东北大学流程工业综合自动化国家重点实验室副教授. 2009 年获得东北大学控制理论与控制工程专业博士学位. 主要研究方向为复杂工业过程自适应控制, 智能解耦控制, 近似动态规划以及工业过程运行控制. 本文通信作者. E-mail: fuyue@mail.neu.edu.cn

Model Predict Control Method Based on Higher-order Observer and Disturbance Compensation Control

Funds: Supported by National Natural Science Foundation of China (61991403, 61991400, 61573090) and Fundamental Research Funds for the Central Universities (N160801001)
  • 摘要: 针对状态不可测、外部干扰未知, 并且状态和输入受限的离散时间线性系统, 将高阶观测器、干扰补偿控制与标准模型预测控制(Model predictive control, MPC)相结合, 提出了一种新的MPC方法. 首先利用高阶观测器同步观测未知状态和干扰, 使得观测误差一致有界收敛;然后基于该干扰估计值设计新的干扰补偿控制方法, 并将该方法与基于状态估计的标准MPC相结合, 实现上述系统的优化控制. 所提出的MPC方法克服了利用现有MPC方法求解具有外部干扰和状态约束的优化控制问题时存在无可行解的局限, 能够保证系统状态在每一时刻都满足约束条件, 并且使系统的输出响应接近采用标准MPC方法控制线性标称系统时得到的输出响应. 最后, 将所提控制方法应用到船舶航向控制系统中, 仿真结果表明了所提方法的有效性和优越性.
  • 图  1  角速度$\gamma$及高阶观测器观测的结果

    Fig.  1  Yaw velocity $\gamma$ and the observed result of higher-order observer

    图  4  干扰$d_{2}$及高阶观测器观测的结果

    Fig.  4  Disturbance $d_{2}$ and observed result of higher-order observer

    图  2  航向角$\psi$及高阶观测器观测的结果

    Fig.  2  Heading angle $\psi$ and the observed result of higher-order observer

    图  3  干扰$ d_{1}$及高阶观测器观测的结果

    Fig.  3  Disturbance $ d_{1}$ and observed result of higher-order observer

    图  5  3种情况下系统的输出响应曲线

    Fig.  5  Output response curves of the system under three conditions

    图  6  3种情况下系统的输入变化曲线

    Fig.  6  Input variation curves of the system under three conditions

    图  7  两种观测方法下系统的输出响应曲线

    Fig.  7  Output response curves of the system under two observation methods

    图  8  两种观测方法下系统输入变化曲线

    Fig.  8  Input variation curves of the system under two observation methods

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出版历程
  • 收稿日期:  2018-10-29
  • 录用日期:  2019-06-12
  • 网络出版日期:  2020-07-10
  • 刊出日期:  2020-07-10

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