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Multi-strategy control to extend the feasibility region for robust model predictive control

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Abstract
This paper proposes a multi-strategy control scheme, which modifies the optimal control problem of robust model predictive control (RMPC) to reduce the on-line computational load or extend the feasible region. The proposed controller is designed to stabilize the system with respect to a subset of the disturbance set. If the disturbance is realized from the rest of the subset, another control strategy is automatically involved to keep the state inside the pre-determined bounded set. The existence of this pre-determined set is proven, and an efficient algorithm is proposed to generate this set. In addition, it is shown that the recursive feasibility and stability of the original RMPC is sustained for the proposed controller. This implies that the proposed method can be applied to a wide range of existing RMPC. Three illustrative examples describe the fundamental ideas and practical advantages. (c) 2022 Elsevier Ltd. All rights reserved.
Author(s)
Tae Hoon OhJong Woo KimSang Hwan SonDong Hwi JeongJong Min Lee
Issued Date
2022
Type
Article
Keyword
Robust controlModel predictive controlUncertain systemsStability
DOI
10.1016/j.jprocont.2022.05.011
URI
https://oak.ulsan.ac.kr/handle/2021.oak/14129
Publisher
JOURNAL OF PROCESS CONTROL
Language
영어
ISSN
0959-1524
Citation Volume
116
Citation Start Page
25
Citation End Page
33
Appears in Collections:
Medicine > Nursing
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