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Thesis

Fast model predictive control

Abstract:

This thesis develops efficient optimization methods for Model Predictive Control (MPC) to enable its application to constrained systems with fast and uncertain dynamics. The key contribution is an active set method which exploits the parametric nature of the sequential optimization problem and is obtained from a dynamic programming formulation of the MPC problem. This method is first applied to the nominal linear MPC problem and is successively extended to linear systems with additive unce...

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Institution:
University of Oxford
Research group:
Control Group
Oxford college:
St John's College
Department:
Mathematical,Physical & Life Sciences Division - Engineering Science

Contributors

Role:
Supervisor
Role:
Supervisor
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Funding agency for:
Johannes Albert Buerger
Publication date:
2013
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:6e296415-f02c-4bc2-b171-3bee80fc081a
Local pid:
ora:7247

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