DocumentCode :
2253810
Title :
Optimal partitioning in distributed model predictive control
Author :
Motee, Nader ; Sayyar-Rodsari, Bijan
Author_Institution :
Dept. of Mech. Eng., Louisiana State Univ., Baton Rouge, LA, USA
Volume :
6
fYear :
2003
fDate :
4-6 June 2003
Firstpage :
5300
Abstract :
In this paper we develop the algorithms for optimal partitioning of a distributed control system into subsystems of manageable size for which control actions are found using model predictive control (MPC) technology. We will first define a realization-invariant weighting matrix to represent the distributed system as a directed graph. We then develop a formulation in which an open loop performance metric is used to partition the distributed system into subsystem in which local MPC problems will be solved. This partitioning however is balanced against the closed loop cost of the control actions for the overall distributed system. Effective algorithms for the distributed control of the large-scale systems are then proposed. Future work will include the study of the effect of the constraints in the partitioning, and the development of efficient problem formulations aimed at improving numerical properties of the proposed control algorithms.
Keywords :
directed graphs; distributed control; large-scale systems; matrix algebra; open loop systems; predictive control; realisation theory; MPC technology; closed loop cost; constraints; directed graph; distributed model predictive control; large-scale system; open loop performance metric; optimal partitioning; realization-invariant weighting matrix; Costs; Distributed control; Measurement; Open loop systems; Optimal control; Partitioning algorithms; Predictive control; Predictive models; Size control; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2003. Proceedings of the 2003
ISSN :
0743-1619
Print_ISBN :
0-7803-7896-2
Type :
conf
DOI :
10.1109/ACC.2003.1242570
Filename :
1242570
Link To Document :
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