Scenario-based, closed-loop model predictive control with application to emergency vehicle scheduling

Model predictive control has been a major success story in process control. More recently, the methodology has been used in other contexts, including automotive engine control, power electronics and telecommunications. Most applications focus on set-point tracking and use single-sequence optimisatio...

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Bibliographic Details
Published inInternational journal of control Vol. 86; no. 8; pp. 1338 - 1348
Main Authors Goodwin, Graham. C., Medioli, Adrian. M.
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis Group 01.08.2013
Taylor & Francis Ltd
Subjects
Ambulances
approximate dynamic programming
Computational fluid dynamics
Emergency vehicles
Heuristic
Mathematical models
Predictive control
re-deployment
scenario-based MPC
Scheduling
stochastic control
Strategy
Tracking
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Summary:Model predictive control has been a major success story in process control. More recently, the methodology has been used in other contexts, including automotive engine control, power electronics and telecommunications. Most applications focus on set-point tracking and use single-sequence optimisation. Here we consider an alternative class of problems motivated by the scheduling of emergency vehicles. Here disturbances are the dominant feature. We develop a novel closed-loop model predictive control strategy aimed at this class of problems. We motivate, and illustrate, the ideas via the problem of fluid deployment of ambulance resources.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0020-7179
1366-5820
DOI:10.1080/00207179.2013.788215