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Solving Linear-Quadratic Optimal Control Problems on Parallel Computers

We discuss a parallel library of efficient algorithms for the solution of linear-quadratic optimal control problems involving largescale systems with state-space dimension up to $O(10^4)$. We survey the numerical algorithms underlying the implementation of the chosen optimal control methods. The approaches considered here are based on invariant and deflating subspace techniques, and avoid the explicit solution of the associated algebraic Riccati equations in case of possible ill-conditioning. Still, our algorithms can also optionally compute the Riccati solution. The major computational task of finding spectral projectors onto the required invariant or deflating subspaces is implemented using iterative schemes for the sign and disk functions. Experimental results report the numerical accuracy and the parallel performance of our approach on a cluster of Intel Itanium-2 processors.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:18609
Date11 September 2006
CreatorsBenner, Peter, Quintana-Ortí, Enrique S., Quintana-Ortí, Gregorio
PublisherTechnische Universität Chemnitz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:preprint, info:eu-repo/semantics/preprint, doc-type:Text
SourcePreprintreihe des Chemnitzer SFB 393, 05-19
Rightsinfo:eu-repo/semantics/openAccess

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