DocumentCode
622579
Title
Decentralised model predictive control with asymptotically positive realness
Author
Tuan, H.D. ; Savkin, Andrey ; Nguyen, Nhan T. ; Nguyen, Hung T.
Author_Institution
Fac. of Eng. & Inf. Technol., Univ. of Technol., Sydney, Ultimo, NSW, Australia
fYear
2013
fDate
12-14 June 2013
Firstpage
822
Lastpage
827
Abstract
This paper presents a novel distributed model predictive control strategy for a large-scale system consisting of interconnected subsystems. A constructive method of online stabilisation that is applicable to the model predictive controllers (MPC) is developed to facilitate the control strategy. The system stability is achievable by the newly introduced asymptotically positive realness constraint (APRC) for MPC. Simulations are provided to demonstrate the efficacy of the presented stability constraint.
Keywords
asymptotic stability; decentralised control; distributed control; large-scale systems; predictive control; APRC; MPC; asymptotically positive realness constraint; decentralised model predictive control; distributed model predictive control strategy; interconnected subsystems; large-scale system; stability constraint; Asymptotic stability; Nickel; Optimization; Predictive control; Silicon; Stability criteria;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation (ICCA), 2013 10th IEEE International Conference on
Conference_Location
Hangzhou
ISSN
1948-3449
Print_ISBN
978-1-4673-4707-5
Type
conf
DOI
10.1109/ICCA.2013.6565006
Filename
6565006
Link To Document