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Thesis

Strategies in robust and stochastic model predictive control

Abstract:

The presence of uncertainty in model predictive control (MPC) has been accounted for using two types of approaches: robust MPC (RMPC) and stochastic MPC (SMPC). Ideal RMPC and SMPC formulations consider closed-loop optimal control problems whose exact solution, via dynamic programming, is intractable for most systems. Much effort then has been devoted to find good compromises between the degree of optimality and computational tractability. This thesis expands on this effort and presents ro...

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Institution:
University of Oxford
Research group:
Control Group
Oxford college:
St Edmund Hall
Department:
Mathematical,Physical & Life Sciences Division - Engineering Science
Role:
Author

Contributors

Role:
Supervisor
Role:
Supervisor
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:2f6bce71-f91f-4d5a-998f-295eff5b089a
Local pid:
ora:9643

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