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Successive Linearization NMPC for a Class of Stochastic Nonlinear Systems

Abstract:

A receding horizon control methodology is proposed for systems with nonlinear dynamics, additive stochastic uncertainty, and both hard and soft (probabilistic) input/state constraints. Jacobian linearization about predicted trajectories is used to derive a sequence of convex optimization problems. Constraints are handled through the construction of tubes and an associated Markov chain model. The parameters defining the tubes are optimized simultaneously with the predicted future control traje...

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Publication status:
Published

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Volume:
384
Pages:
249-262
Host title:
NONLINEAR MODEL PREDICTIVE CONTROL: TOWARDS NEW CHALLENGING APPLICATIONS
Publication date:
2009-01-01
DOI:
ISSN:
0170-8643
Source identifiers:
63700
ISBN:
9783642010934
Keywords:
Pubs id:
pubs:63700
UUID:
uuid:3e51db40-be58-477e-b50e-d7b75a840efa
Local pid:
pubs:63700
Deposit date:
2012-12-19

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