Explicit model predictive control: A connected-graph approach

详细信息    查看全文

• 作者：Richard Oberdieck^a ; ^b ; ^{richard.oberdieck11@imperial.ac.uk}Author Vitae ; Nikolaos A. Diangelakis^a ; ^b ; ^{nikos@tamu.edu}Author Vitae ; Efstratios N. Pistikopoulos^b ; ^{stratos@tamu.edu}Author Vitae
• 关键词：Explicit MPC ; Multi-parametric programming ; Combined heat and power
• 刊名：Automatica
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：76
• 期：Complete
• 页码：103-112
• 全文大小：861 K
• 卷排序：76

文摘

The ability to solve model predictive control (MPC) problems of linear time-invariant systems explicitly and offline via multi-parametric quadratic programming (mp-QP) has become a widely used methodology. The most efficient approaches used to solve the underlying mp-QP problem are either based on combinatorial considerations, which scale unfavorably with the number of constraints, or geometrical considerations, which require heuristic tuning of the step-size and correct identification of the active set. In this paper, we describe a novel algorithm which unifies these two types of approaches by showing that the solution of a mp-QP problem is given by a connected graph, where the nodes correspond to the different optimal active sets over the parameter space. Using an extensive computational study, as well as the explicit MPC solution of a combined heat and power system, the merits of the proposed algorithm are clearly highlighted.