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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
Department:
Oxford, MPLS, Engineering Science
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Institution:
University of Oxford
Department:
Oxford, MPLS, Engineering Science
Volume:
384
Pages:
249-262
Publication date:
2009
DOI:
ISSN:
0170-8643
URN:
uuid:3e51db40-be58-477e-b50e-d7b75a840efa
Source identifiers:
63700
Local pid:
pubs:63700
ISBN:
978-3-642-01093-4

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