Abstract
This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
Original language | English (US) |
---|---|
Pages (from-to) | 183-203 |
Number of pages | 21 |
Journal | Computational Management Science |
Volume | 9 |
Issue number | 2 |
DOIs | |
State | Published - Apr 21 2012 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: The financial support of European Research Council (MOBILE ERC AdvancedGrant,no:226462),EPSRC(ProjectsGR/T02560/01,EP/E047017,EP/E054285/1)andEuropeanCommis-sion (PROMATCH Marie Curie MRTN-CT-2004-512441, PRISM Marie Curie MTKI-CT-2004-512233,DIAMANTE ToK Project MTKI-CT-2005-IAP-029544, HY2SEP RTD Project 019887, CONNECTCOOP-CT-2006-031638), Air Products, CPSE Industrial Consortium and KAUST is kindly acknowledged.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.