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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Authors
Contributors
+ Kouvaritakis, B
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
+ Cannon, M
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Bibliographic Details
- Publication date:
- 2014
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- Oxford University, UK
Item Description
- Language:
- English
- Keywords:
- Subjects:
- UUID:
-
uuid:2f6bce71-f91f-4d5a-998f-295eff5b089a
- Local pid:
- ora:9643
- Deposit date:
- 2015-01-05
Terms of use
- Copyright holder:
- Munoz Carpintero, D
- Copyright date:
- 2014
- Notes:
- This thesis is not currently available in ORA.
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