DocumentCode
184357
Title
Distributed Model Predictive Control for MLD systems: Application to freeway ramp metering
Author
Ferrara, A. ; Sacone, Simona ; Siri, Silvia
Author_Institution
Dept. of Electr., Univ. of Pavia, Pavia, Italy
fYear
2014
fDate
4-6 June 2014
Firstpage
5294
Lastpage
5299
Abstract
This paper deals with mixed logical dynamical systems controlled via model predictive schemes. For this class of systems a centralized MPC approach is firstly introduced, in which the finite horizon optimal control problem is a mixed-integer quadratic programming problem aiming at minimizing the deviations of the system variables from their equilibrium points. Since the application in real time of these MPC schemes is sometimes limited because of the high computational load necessary to solve the finite horizon optimal control problem, a distributed MPC scheme is proposed, characterized by two different and alternative algorithms. An important application is then introduced to assess the proposed approaches, i.e. ramp metering freeway traffic control. Referring to this applicative case, the two distributed control algorithms are compared, via simulation, with the centralized MPC scheme and with a completely decentralized one.
Keywords
distributed control; integer programming; optimal control; predictive control; quadratic programming; road traffic control; MLD systems; centralized MPC approach; distributed MPC scheme; distributed model predictive control; equilibrium points; finite horizon optimal control problem; freeway ramp metering; mixed logical dynamical systems; mixed-integer quadratic programming problem; Clustering algorithms; Cost function; Decentralized control; Optimal control; Traffic control; Vectors; Control applications; Large scale systems; Predictive control for nonlinear systems;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6859063
Filename
6859063
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