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基于多变量广义预测控制的不稳定系统控制结构选择方法

许锋 魏小丽 任丽红 罗雄麟

许锋, 魏小丽, 任丽红, 罗雄麟. 基于多变量广义预测控制的不稳定系统控制结构选择方法. 自动化学报, 2013, 39(9): 1547-1551. doi: 10.3724/SP.J.1004.2013.01547
引用本文: 许锋, 魏小丽, 任丽红, 罗雄麟. 基于多变量广义预测控制的不稳定系统控制结构选择方法. 自动化学报, 2013, 39(9): 1547-1551. doi: 10.3724/SP.J.1004.2013.01547
XU Feng, WEI Xiao-Li, REN Li-Hong, LUO Xiong-Lin. A Control Structure Selection Method Based on Multivariable Generalized Predictive Control for Unstable Processes. ACTA AUTOMATICA SINICA, 2013, 39(9): 1547-1551. doi: 10.3724/SP.J.1004.2013.01547
Citation: XU Feng, WEI Xiao-Li, REN Li-Hong, LUO Xiong-Lin. A Control Structure Selection Method Based on Multivariable Generalized Predictive Control for Unstable Processes. ACTA AUTOMATICA SINICA, 2013, 39(9): 1547-1551. doi: 10.3724/SP.J.1004.2013.01547

基于多变量广义预测控制的不稳定系统控制结构选择方法

doi: 10.3724/SP.J.1004.2013.01547
基金项目: 

国家自然科学基金(21006127, 20976193)资助

详细信息
    作者简介:

    许锋 中国石油大学(北京)自动化研究所讲师.主要研究方向为过程控制与实时优化,过程系统工程. E-mail:xufengfxzt@sohu.com

A Control Structure Selection Method Based on Multivariable Generalized Predictive Control for Unstable Processes

Funds: 

Supported by National Natural Science Foundation of China (21006127, 20976193)

  • 摘要: 对于多输入多输出系统, 在控制系统设计时首先要对被控变量和操纵变量进行控制结构选择. Bristol提出的相关增益矩阵(Relative gain array, RGA)法, 以及学者们后来提出的各种改进方法, 都只适用于稳定系统. 本文针对不稳定系统, 基于多变量广义预测控制(Generalized predictive control, GPC)的闭环控制律提出了一种控制结构的变量匹配准则. 通过对预测时域、控制时域等各个参数的优化选择, 使系统闭环稳定; 由闭环控制律得到被控变量期望值与操纵变量的相关性矩阵, 以此得出控制结构的变量配对方案. 通过实例研究表明, 对于开环不稳定系统, 该方法可以得出正确的变量配对结果.
  • [1] Xu Feng, Luo Xiong-Lin. Regulatory control structure selection in chemical process with mathematical programming. Computers and Applied Chemistry, 2007, 24(9): 1166-1172 (许锋, 罗雄麟. 基于数学规划的化工过程常规控制系统的结构选择. 计算机与应用化学, 2007, 24(9): 1166-1172)
    [2] Ahmadi T A, Mohammadi S A. A model free dynamic criterion for online input-output pairing. In: Proceedings of the 2011 Australian Control Conference. Melbourne, Australia: AUCC, 2011. 531-536
    [3] Xiong Q, Cai W J, He M J. A practical loop pairing criterion for multivariable processes. Journal of Process Control, 2005, 15(7): 741-747
    [4] Monshizadeh-Naini N, Fatehi A, Khaki-Sedigh A. Input-output pairing using effective relative energy array. Industrial & Engineering Chemistry Research, 2009, 48(15): 7137-7144
    [5] He M J, Cai W J, Ni W, Xie L H. RNGA based control system configuration for multivariable processes. Journal of Process Control, 2009, 19(6): 1036-1042
    [6] Cheng Y F, Li S Y. A new pairing method for multivariable processes. Industrial & Engineering Chemistry Research, 2010, 49(13): 6115-6124
    [7] McAvoy T, Arkun Y, Chen R, Robinson D, Schnelle P D. A new approach to defining a dynamic relative gain. Control Engineering Practice, 2003, 11(8): 907-914
    [8] Lee J, Edgar T F. Dynamic interaction measures for decentralized control of multivariable processes. Industrial & Engineering Chemistry Research, 2004, 43(2): 283-287
    [9] Meeuse F M, Huesman A E M. Analyzing dynamic interaction of control loops in the time domain. Industrial & Engineering Chemistry Research, 2002, 41(18): 4585-4590
    [10] Renanto H, Avon T H, Joko L. Comparison of steady state and dynamic interaction measurements in multiloop control systems. ASEAN Journal of Chemical Engineering, 2005, 5(1): 1-15
    [11] Hovd M, Scogestad S. Pairing criteria for decentralized control of unstable plants. Industrial & Engineering Chemistry, 1994, 33(9): 2134-2139
    [12] Huang H P, Lin F Y, Jeng J C. Multi-loop PID controllers design for MIMO processes containing integrator(s). Journal of Chemical Engineering of Japan, 2005, 38(9): 742-756
    [13] Witcher M F, McAvoy T J. Interacting control system: steady-state and dynamic measurement of interaction. ISA Transactions, 1977, 16(3): 35-41
    [14] Hu W H, Cai W J, Xiao G X. Relative gain array for MIMO processes containing integrators and/or differentiators. In: Proceedings of the 11th International Conference on Control Automation Robotics & Vision (ICARCV). Singapore: IEEE, 2010. 231-235
    [15] Ding Bao-Cang. Theory and Method of Predictive Control. Beijing: China Machine Press, 2008. 176-183(丁宝苍. 预测控制的理论与方法. 北京: 机械工业出版社, 2008. 176-183)
    [16] Shu Di-Qian. Predictive Control System and Application. Beijing: China Machine Press, 2001. 97-102 (舒迪前. 预测控制系统及其应用. 北京: 机械工业出版社, 2001. 97-102)
    [17] Hu Pin-Hui. Multivariable State Feedback Model Predictive Control and Its Application [Ph.D. dissertation], China University of Petroleum, China, 1999 (胡品慧. 多变量状态反馈预测控制及应用[博士学位论文], 中国石油大学, 中国, 1999)
    [18] Zhu Hong-Ping, Li Run-Qiu. Optimization design of PID parameter based on Matlab. Ordnance Industry Automation, 2004, 23(1): 39-40(朱红平, 李润求. 基于Matlab的PID参数最优化设计. 兵工自动化, 2004, 23(1): 39-40)
    [19] Hu W H, Cai W J, Xiao G X. Decentralized control system design for MIMO processes with integrators/differentiators. Industrial & Engineering Chemistry Research, 2010, 49(24): 12521-12528
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出版历程
  • 收稿日期:  2012-05-11
  • 修回日期:  2012-08-31
  • 刊出日期:  2013-09-20

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