A dynamic programming based approach for explicit model predictive control of hybrid systems

This work presents an algorithm for explicit model predictive control of hybrid systems based on recent developments in constrained dynamic programming and multi-parametric programming. By using the proposed approach, suitable for problems with linear cost function, the original model predictive con...

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Veröffentlicht in:Computers & chemical engineering Jg. 72; S. 126 - 144
Hauptverfasser: Rivotti, Pedro, Pistikopoulos, Efstratios N.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 02.01.2015
Schlagworte:
Algorithms
Cost function
Dynamic programming
Hybrid systems
Mathematical models
Methodology
Model predictive control
Multi-parametric programming
Predictive control
Programming
Robust model predictive control
Model predictive control
Hybrid systems
Multi-parametric programming
Dynamic programming
Robust model predictive control
ISSN:0098-1354, 1873-4375
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Zusammenfassung:This work presents an algorithm for explicit model predictive control of hybrid systems based on recent developments in constrained dynamic programming and multi-parametric programming. By using the proposed approach, suitable for problems with linear cost function, the original model predictive control formulation is disassembled into a set of smaller problems, which can be efficiently solved using multi-parametric mixed-integer programming algorithms. It is also shown how the methodology is applied in the context of explicit robust model predictive control of hybrid systems, where model uncertainty is taken into account. The proposed developments are demonstrated through a numerical example where the methodology is applied to the optimal control of a piece-wise affine system with linear cost function.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2014.06.003