期刊
JOURNAL OF PROCESS CONTROL
卷 22, 期 6, 页码 975-983出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2012.05.002
关键词
Off-line; Robust MPC; Polyhedral invariant sets; Stabilizable region
资金
- Higher Education Research Promotion and National Research University Project of Thailand, Office of the Higher Education Commission [EN636A]
In this paper, an off-line synthesis approach to robust model predictive control (MPC) using polyhedral invariant sets is presented. Most of the computational burdens are moved off-line by computing a sequence of state feedback control laws corresponding to a sequence of polyhedral invariant sets. At each sampling time, the smallest polyhedral invariant set that the currently measured state can be embedded is determined. The corresponding state feedback control law is then implemented to the process. The controller design is illustrated with two examples. Comparisons between the proposed algorithm and an ellipsoidal off-line robust MPC algorithm have been undertaken. The proposed algorithm yields a substantial expansion of the stabilizable region. Therefore, it can achieve less conservative result as compared to an ellipsoidal off-line robust MPC algorithm. (C) 2012 Elsevier Ltd. All rights reserved.
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