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Successive constrained optimization and interpolation in non-linear model based predictive control

Abstract:
Interpolation involving constrained optima offers distinctive advantages for linear and non-linear model based predictive control algorithms. For non-linear systems the computation of minima is non-trivial and sub-optimal solutions can be sought through linearization about particular trajectories. Here we show that successive linearizations and locally constrained optimizations can, at a modest extra computation, lead to significant improvements.
Publication status:
Published

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Publisher copy:
10.1080/002071700219669

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Journal:
INTERNATIONAL JOURNAL OF CONTROL More from this journal
Volume:
73
Issue:
4
Pages:
312-316
Publication date:
2000-03-10
DOI:
EISSN:
1366-5820
ISSN:
0020-7179


Language:
English
Pubs id:
pubs:62904
UUID:
uuid:1b7c6541-82a9-47f2-a831-a95b393f2ce1
Local pid:
pubs:62904
Source identifiers:
62904
Deposit date:
2013-11-17

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