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 :
بازگشت