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

Cited 3 time in Web of Science Cited 4 time in Scopus
Authors

Oh, Tae Hoon; Kim, Jong Woo; Son, Sang Hwan; Jeong, Dong Hwi; Lee, Jong Min

Issue Date
2022-08
Publisher
Butterworth Scientific Ltd.
Citation
Journal of Process Control, Vol.116, pp.25-33
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.
ISSN
0959-1524
URI
https://hdl.handle.net/10371/184496
DOI
https://doi.org/10.1016/j.jprocont.2022.05.011
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