动态输出反馈鲁棒模型预测控制

平续斌; 丁宝苍; 韩崇昭

doi:10.3724/SP.J.1004.2012.00031

动态输出反馈鲁棒模型预测控制

doi: 10.3724/SP.J.1004.2012.00031

1.
西安交通大学智能网络与网络安全教育部重点实验室机械制造系统工程国家重点实验室电子与信息工程学院综合自动化研究所西安 710049

详细信息

通讯作者:
丁宝苍

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出版历程
- 收稿日期: 2011-02-28
- 修回日期: 2011-08-09
- 刊出日期: 2012-01-20

Dynamic Output Feedback Robust Model Predictive Control

1.
Ministry of Education Key Laboratory for Intelligent Networks and Network Security, State Key Laboratory for Manufacturing Systems Engineering, Institute of Integrated Automation, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049

摘要

摘要: 研究了具有多包不确定性和有界噪声的系统的动态输出反馈鲁棒模型预测控制的综合方法.系统为准线性参数时变的,即系统时变参数在当前时刻精确已知,但在将来时刻未知.采用二次有界概念刻画扩展闭环系统的稳定性.本文主要创新在于提出了一种辅助优化方法,从而为下个采样时刻的主优化问题提供可靠的真实状态的界.通过连续搅拌釜式反应器控制系统验证了该方法的有效性.
- 动态输出反馈 /
- 模型预测控制 /
- 不确定系统 /
- 二次有界
Abstract: This paper addresses the synthesis approach of dynamic output feedback robust model predictive control for systems with both polytopic uncertainty and bounded disturbance. The system is quasi-linear parameter varing, i.e., the time-varing parameters of the system are exactly known at the current time but unknown in the future. The notion of quadratic boundedness is utilized to characterize the stability properties of the augmented closed-loop system. The primary contribution of this paper is to propose a method for the auxiliary optimization to provide reliable bounds of true state for the main optimization problem at the next sampling time. A continuous stirred tank reactor control system is given to illustrate the effectiveness of the approach.
- Dynamic output feedback /
- model predictive control /
- uncertain system /
- quadratic boundedness

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参考文献(1)

[1]

Xi Yu-Geng,Li De-Wei. Fundamental philosophy and status of qualitative synthesis of model predictive control. Acta Automatica Sinica,2008,34(10):1225-1234(席裕庚,李德伟. 预测控制定性综合理论的基本思路和研究现状. 自动化学报,2008,34(10):1225-1234)[2] Ding B C. Feasibility,optimality and computational complexity of robust model predictive control. In:Proceedings of the Chinese Control and Decision Conference. Yantai,China:IEEE,2008. 3052-3057[3] Kothare M V,Balakrishnan V,Morari M. Robust constrained model predictive control using linear matrix inequalities. Automatica,1996,32(10):1361-1379[4] Ding B C,Xi Y G,Cychowski M T,O'Mahony T. A synthesis approach for output feedback robust constrained model predictive control. Automatica,2008,44(1):258-264[5] Ding B C,Xie L H. Robust model predictive control via dynamic output feedback. In:Proceedings of the 7th World Congress on Intelligent Control and Automation. Chongqing,China:IEEE,2008. 3388-3393[9] Alessandri A,Baglietto M,Battistelli G. On estimation error bounds for receding-horizon filters using quadratic boundedness. IEEE Transactions on Automatic Control,2004,49(8):1350-1355[10] Alessandri A,Baglietto M,Battistelli G. Design of state estimators for uncertain linear systems using quadratic boundedness. Automatica,2006,42(3):497-502[6] Ding B C,Xie L H,Xue F Z. Improving robust model predictive control via dynamic output feedback. In:Proceedings of the Chinese Control and Decision Conference. Guilin,China:IEEE,2009. 2116-2121[7] Ding B C,Xie L H. Dynamic output feedback robust model predictive control with guaranteed quadratic boundedness. In:Proceedings of the 48th IEEE Conference on Decision and Control Held Jointly with the 28th Chinese Control Conference. Shanghai,China:IEEE,2009. 8034-8039[8] Ding B C. Constrained robust model predictive control via parameter-dependent dynamic output feedback. Automatica,2010,46(9):1517-1523[11] Ghaoui L E,Oustry F,AitRami M. A cone complementarity linearization algorithm for static output-feedback and related problems. IEEE Transactions on Automatic Control,1997,42(8):1171-1176

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