Multiplexed model predictive control

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• 作者：Keck Voon Ling^a ; ¹ ; ^{ekvling@ntu.edu.sg}  ; [Author Vitae] ; Jan Maciejowski^b ; ^{jmm@eng.cam.ac.uk}  ; [Author Vitae] ; Arthur Richards^c ; ^{arthur.richards@bristol.ac.uk}  ; [Author Vitae] ; Bing Fang Wu^a ; ^{bingfang_wu@pmail.ntu.edu.sg}  ; [Author Vitae]
• 关键词：Predictive control ; Distributed control ; Multivariable control ; Periodic systems ; Constrained control
• 刊名：Automatica
• 出版年：2012
• 出版时间：February, 2012
• 年：2012
• 卷：48
• 期：2
• 页码：396-401
• 全文大小：541 K

文摘

This paper proposes a form of MPC in which the control variables are moved asynchronously. This contrasts with most MIMO control schemes, which assume that all variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The Multiplexed MPC (MMPC) scheme described in this paper solves the MPC problem for each subsystem sequentially, and updates subsystem controls as soon as the solution is available, thus distributing the control moves over a complete update cycle. The resulting computational speed-up allows faster response to disturbances, which may result in improved performance, despite finding sub-optimal solutions to the original problem. This paper describes nominal and robust MMPC, states some stability results, and demonstrates the effectiveness of MMPC through two examples.