基于多步控制策略的混合H2/H∞鲁棒预测控制器设计

黄鹤; 李德伟; 席裕庚

doi:10.3724/SP.J.1004.2012.00944

基于多步控制策略的混合H₂/H_∞鲁棒预测控制器设计

doi: 10.3724/SP.J.1004.2012.00944

1.
上海交通大学自动化系系统控制与信息处理教育部重点实验室上海 200240

详细信息

通讯作者:
李德伟,上海交通大学自动化系副研究员.分别于1993年和2009年在上海交通大学自动化系获得学士学位和博士学位.主要研究方向为预测控制理论与算法.

计量
- 文章访问数: 2376
- HTML全文浏览量: 68
- PDF下载量: 1008
- 被引次数: 0
出版历程
- 收稿日期: 2010-11-12
- 修回日期: 2011-02-21
- 刊出日期: 2012-06-20

On Design of Mixed H₂/H_∞ RMPC Based on Multi-step Control Strategy

1.
Key Laboratory of System Control and Information Processing of Ministry of Education, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240

摘要

摘要: 针对具有外界扰动的线性定常(Linear time invariant, LTI)系统, 本文研究了其鲁棒预测控制器(Robust model predictive control, RMPC)的设计方法. 设计采用了混合的H2/H∞控制方法以有效地兼顾系统的抗干扰能力和闭环控制性能. 同时, 为了降低设计的保守性, 设计利用闭环多步控制策略以扩大控制器的可行范围, 改善系统控制性能. 进而, 为了便于实际实施, 提出该RMPC的简化设计, 通过将大部分在线计算量离线完成以降低鲁棒预测控制器的在线计算量.
- 鲁棒预测控制 /
- 多步控制策略 /
- 混合H2/H∞ /
- 线性矩阵不等式
Abstract: With consideration of the linear time invariant (LTI) system with additive disturbance, the design of robust model predictive control (RMPC) is studied. In order to balance the capability to reject the disturbance and control performance, the mixed H2/H∞ approach is adopted. Meanwhile, the multi-step control set is utilized to reduce the conservativeness of the design, which results in the improved control performance and the larger feasible region. Furthermore, in order to make the proposed design easy to implement, an efficient version of RMPC is also developed, where the main computation of RMPC is transferred to be completely off-line to reduce the online computational burden.
- Robust model predictive control (RMPC) /
- multi-step control strategy /
- mixed H2/H∞ /
- linear matrix inequalities (LMIs)

HTML全文

参考文献(1)

[1]

Mayne D Q, Rawlings J B, Rao C V, Scokaert P O M. Constrained model predictive control: stability and optimality. Automatica, 2000, 36(6): 789-814[2] Qin S J, Badgwell T A. A survey of industrial model predictive control technology. Control Engineering Practice, 2003, 11(7): 733-764[3] Xi Y G, Li D W. Fundamental philosophy and status of qualitative synthesis of model predictive control. Acta Automatica Sinica, 2008, 34(10): 1225-1234[4] Kothare M V, Balakrishnan V, Morari M. Robust constrained model predictive control using linear matrix inequalities. Automatica, 1996, 32(10): 1361-1379[5] Cuzzola F A, Geromel J C, Morari M. An improved approach for constrained robust model predictive control. Automatica, 2002, 38(7): 1183-1189[6] Mao W J. Robust stabilization of uncertain time-varying discrete systems and comments on “an improved approach for constrained robust model predictive control”. Automatica, 2003, 39(6): 1109-1112[7] Li D W, Xi Y G. Design of robust model predictive control based on multi-step control set. Acta Automatica Sinica, 2009, 35(4): 433-437[8] Li D W, Xi Y G, Zheng P Y. Constrained robust feedback model predictive control for uncertain systems with polytopic description. International Journal of Control, 2009, 82(7): 1267-1274[9] Wang J, Liu Z Y, Chen H, Yu S Y, Pei R. H∞ Output feedback control of constrained systems via moving horizon strategy. Acta Automatica Sinica, 2007, 33(11): 1176-1181[10] Xie L, Soh Y C. Guaranteed cost control of uncertain discrete-time systems. Control Theory and Advanced Technology, 1995, 10(4): 1235-1251[11] Dhawan A, Kar H. Optimal guaranteed cost control of 2-D discrete uncertain systems: an LMI approach. Signal Processing, 2007, 87(12): 3075-3085[12] Yu L. Optimal guaranteed cost control of linear uncertain system: an LMI approach. Journal of Control Theory and Application, 2000, 17(3): 423-428[13] Orukpe P E, Jaimoukha I M, El-Zobaidi H M H. Model predictive control based on mixed H2/H∞ control approach. In: Proceedings of the 2007 American Control Conference (ACC). New York, USA: IEEE, 2007. 6147-6150[14] Orukpe P E, Zheng Xiang, Jaimoukha I M, Zolotas A C, Goodall R M. Model predictive control based on mixed H2/H∞ control approach for active vibration control of railway vehicles. Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility, 2008, 46(S1): 151- 160[15] Gahinet P, Nemirovski A, Laub A J, Chilali M. LMI control toolbox for use with Matlab. User's Guide. Natick, MA, USA: The Math Works Inc, 1995

施引文献

资源附件(0)

访问统计