File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

오태훈

Oh, Tae Hoon
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

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

Author(s)
Oh, Tae HoonKim, Jong WooSon, Sang HwanJeong, Dong HwiLee, Jong Min
Issued Date
2022-08
DOI
10.1016/j.jprocont.2022.05.011
URI
https://scholarworks.unist.ac.kr/handle/201301/81574
Citation
JOURNAL OF PROCESS CONTROL, v.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.
Publisher
ELSEVIER SCI LTD
ISSN
0959-1524
Keyword (Author)
Robust controlModel predictive controlUncertain systemsStability
Keyword
OPTIMIZATIONUNCERTAINTYALGORITHMSETSMPC

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.