2.765

2022影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

具有解耦性能的离散时间线性多变量系统最优跟踪控制

富月 陈威

富月, 陈威. 具有解耦性能的离散时间线性多变量系统最优跟踪控制. 自动化学报, 2022, 48(8): 1931−1939 doi: 10.16383/j.aas.c190748
引用本文: 富月, 陈威. 具有解耦性能的离散时间线性多变量系统最优跟踪控制. 自动化学报, 2022, 48(8): 1931−1939 doi: 10.16383/j.aas.c190748
Fu Yue, Chen Wei. Optimal tracking control method for discrete-time linear multivariable systems with decoupling performance. Acta Automatica Sinica, 2022, 48(8): 1931−1939 doi: 10.16383/j.aas.c190748
Citation: Fu Yue, Chen Wei. Optimal tracking control method for discrete-time linear multivariable systems with decoupling performance. Acta Automatica Sinica, 2022, 48(8): 1931−1939 doi: 10.16383/j.aas.c190748

具有解耦性能的离散时间线性多变量系统最优跟踪控制

doi: 10.16383/j.aas.c190748
基金项目: 国家自然科学基金(61991403, 61991400)和辽宁省教育厅创新人才项目(ZX20200070)资助
详细信息
    作者简介:

    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

    陈威:天辰工程有限公司工程师. 分别于2018 年获得河北工业大学学士学位, 2021年获得东北大学硕士学位. 主要研究方向为解耦控制和最优控制.E-mail: chenwei0323@126.com

Optimal Tracking Control Method for Discrete-time Linear Multivariable Systems With Decoupling Performance

Funds: Supported by National Natural Science Foundation of China (61991403, 61991400) and Innovative Talent Project of Liaoning Education Committee (ZX20200070)
More Information
    Author Bio:

    FU Yue Associate professor at the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University. She received her Ph.D. degree from Northeastern University in 2009. Her research interest covers adaptive control, intelligent decoupling control, approximate dynamic programming, and industrial operational control. Corresponding author of this paper

    CHEN Wei Engineer at Tianchen Corporation. He received his bachelor degree from Hebei University of Technology in 2018 and received his master degree from Northeastern University in 2021. His research interest covers decoupling control and optimal control

  • 摘要: 在传统线性二次跟踪控制方法的基础上, 针对一类具有强耦合特性的离散时间线性多变量系统, 提出了一种具有解耦性能的最优跟踪控制方法. 首先为实现解耦, 将耦合项作为可测干扰, 基于零和博弈思想提出了一种新的性能指标; 然后针对该性能指标, 利用极小值原理设计最优跟踪控制器, 通过适当加权矩阵的选择, 同步实现解耦和跟踪; 最后进行仿真实验, 仿真结果表明了该方法的有效性以及在最优性能等方面的优越性.
  • 图  1  本文所提方法系统状态输出

    Fig.  1  Output curves by using the method proposed in this paper

    图  2  本文所提方法控制输入

    Fig.  2  Input curves by using the method proposed in this paper

    图  3  传统LQT方法系统状态输出

    Fig.  3  Output curves by using the conventional LQT method

    图  4  传统LQT方法控制输入

    Fig.  4  Input curves by using the conventional LQT method

    图  5  传统LQT方法系统状态输出

    Fig.  5  Output curves by using the conventional LQT method

    图  6  传统LQT方法控制输入

    Fig.  6  Input curves by using the conventional LQT method

    图  7  第1组参数下, 2种策略的最优性能比较

    Fig.  7  Comparison of the performance under the first set of parameters

    图  8  第2组参数下, 2种策略的最优性能比较

    Fig.  8  Comparison of the performance under the second set of parameters

    A1  基于神经网络补偿的不确定性系统状态跟踪曲线

    A1  Tracking curve of uncertain system based on neural network compensation

  • [1] Tien L, Schaffer A. Robust adaptive tracking control based on state feedback controller with integrator terms for elastic joint robots with uncertain parameters. IEEE Transactions on Control Systems Technology, 2018, 26(6): 2259−2267 doi: 10.1109/TCST.2017.2749564
    [2] Qiu B, Wang G, Fan Y, Mu D, Sun X. Robust adaptive trajectory linearization control for tracking control of surface vessels with modeling uncertainties under input saturation. IEEE Access, 2018, 7: 5057−5070
    [3] Chai R, Savvaris A, Tsourdos A, Chai S, Xia Y. Optimal tracking guidance for aeroassisted spacecraft reconnaissance mission based on receding horizon control. IEEE Transactions on Aerospace and Electronic Systems, 2018, 54(4): 1575−1588 doi: 10.1109/TAES.2018.2798219
    [4] Fujimoto H, Kawamura A. Perfect tracking digital motion control based on two-degree-of-freedom multi-rate feedforward control. In: Proceedings of the International Workshop on Advanced Motion Control. Coimbra, Portugal: IEEE, 1998. 322−327
    [5] Fujimoto H, Hori Y, Kawamura A. Perfect tracking control based on multirate feedforward control with generalized sampling Periods. IEEE Transactions on Industrial Electronics, 2001, 48(3): 636−644 doi: 10.1109/41.925591
    [6] Liu L, Huang J. Global robust output regulation of output feedback systems with unknown high-frequency gain sign. IEEE Transactions on Automatic Control, 2006, 51(4): 625−631 doi: 10.1109/TAC.2006.872752
    [7] Li T, Wang D, Feng G, Tong S. A DSC approach to robust adaptive NN tracking control for strict−feedback nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics, 2010, 40(3): 915−927 doi: 10.1109/TSMCB.2009.2033563
    [8] Liu Y, Wang W, Tong S, Liu Y. Robust adaptive tracking control for nonlinear systems based on bounds of fuzzy approximation parameters. IEEE Transactions on Systems, Man, and Cybernetics, 2010, 40(1): 170−184 doi: 10.1109/TSMCA.2009.2030164
    [9] Wang N, Sun J, Er M. Tracking-error-based universal adaptive fuzzy control for output tracking of nonlinear systems with completely unknown dynamics. IEEE Transactions on Fuzzy Systems, 2018, 26(2): 869−883 doi: 10.1109/TFUZZ.2017.2697399
    [10] Lewis F, Vrabie D, Syrmos V. Optimal Control, New Jersey: John Wiley & sons, Inc, 2012. 190−195
    [11] Fu Y, Hong C, Li J. Optimal decoupling control method and its application to a ball mill coal−pulverizing system Acta Automatica Sinica, 2018, 5(6): 1035−1043 doi: 10.1109/JAS.2018.7511219
    [12] Modares H, Lewis F. Linear quadratic tracking control of partially−unknown continuous−time systems using reinforcement learning. IEEE Transactions on Automatic Control, 2014, 59(11): 3051−3056 doi: 10.1109/TAC.2014.2317301
    [13] Kiumarsi B, Lewis F, Bagher M, Sistani N, Karimpour A. Optimal tracking control of unknown discrete−time linear systems using input−output measured data. IEEE Transactions on Cybernetics, 2015, 45(12): 2770−2779 doi: 10.1109/TCYB.2014.2384016
    [14] Park Y, Choi M, Lee K. An optimal tracking neuro controller for nonlinear dynamic systems. IEEE Transactions on Neural Networks, 1996, 7(5): 1099−1110 doi: 10.1109/72.536307
    [15] Zhang H, Wei Q, Luo Y. A novel infinite−time optimal tracking control scheme for a class of discrete−time nonlinear systems via the greedy HDP iteration algorithm. IEEE Transactions on Systems, Man, and Cybernetics, 2008, 38(4): 937−942 doi: 10.1109/TSMCB.2008.920269
    [16] Zhang H, Song R, Wei Q, Zhang T. Optimal tracking control for a class of nonlinear discrete−time systems with time delays based on heuristic dynamic programming. IEEE Transactions on Neural Networks, 2011, 22(12): 1851−1862 doi: 10.1109/TNN.2011.2172628
    [17] Zhang H, Cui L, Zhang X, Luo Y. Data−driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method. IEEE Transactions on Neural Networks, 2011, 22(12): 2226−2236 doi: 10.1109/TNN.2011.2168538
    [18] 王康, 李晓理, 贾超, 宋桂芝. 基于自适应动态规划的矿渣微粉生产过程跟踪控制. 自动化学报, 2016, 42(10): 1542−1551

    Wang Kang, Li Xiao−Li, Jia Chao, Song Gui−Zhi. Optimal tracking vontrol for slag grinding process based on adaptive dynamic programming Acta Automatica Sinica, 2016, 42(10): 1542−1551
    [19] 袁兆麟, 何润姿, 姚超, 李佳, 班晓娟, 李潇睿. 基于强化学习的浓密机底流浓度在线控制算法. 自动化学报, 2021, 47(7):1558-1571

    Yuan Zhao−Lin, He Run−Zi, Yao Chao, Li Jia, Ban Xiao−Juan, Li Xiao−Rui. An online concentration control algorithm for underflow of thickener based on reinforcement learning. Acta Automatica Sinica, 2021, 47(7):1558-1571
    [20] 郭壁垒, 苏宏业, 柳向斌, 刘之涛. 带有非线性不确定奇异系统的积分滑模控制. 控制理论与应用, 2010, 27(7): 873−879

    GUO Bi−Lei, SU Hong−Ye, LIU Xiang−Bin, LIU Zhi−Tao. Integral sliding mode control for singular systems with nonlinear uncertainties. Control Theory & Applications, 27(7): 873−879
  • 加载中
图(9)
计量
  • 文章访问数:  580
  • HTML全文浏览量:  88
  • PDF下载量:  246
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-10-29
  • 录用日期:  2020-03-11
  • 网络出版日期:  2022-07-12
  • 刊出日期:  2022-06-01

目录

    /

    返回文章
    返回