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Time domain decomposition methods fo...

Comas, Agata.

Time domain decomposition methods for second-order linear quadratic optimal control problems.

紀錄類型:	書目-電子資源 : 單行本
正題名/作者:	Time domain decomposition methods for second-order linear quadratic optimal control problems./
作者:	Comas, Agata.
面頁冊數:	201 p.
附註:	Source: Masters Abstracts International, Volume: 42-05, page: 1725.
Contained By:	Masters Abstracts International42-05.
標題:	Mathematics. -
電子資源:	Download fulltext (下載全文)
ISBN:	049623837X

Time domain decomposition methods for second-order linear quadratic optimal control problems.
Comas, Agata.

Time domain decomposition methods for second-order linear quadratic optimal control problems. - 201 p.

Source: Masters Abstracts International, Volume: 42-05, page: 1725.

Thesis (M.A.)--Rice University, 2004.

Optimal control problems governed by time-dependent differential equations lead to large scale problems. Their numerical solution is challenging due to large storage demands resulting from the coupling in time of the solution of the governing (state) equation and the so-called adjoint equation.

ISBN: 049623837XSubjects--Topical Terms:

146772
Mathematics.

Time domain decomposition methods for second-order linear quadratic optimal control problems.
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100 1 $a Comas, Agata. $3 1000005712
245 1 0 $a Time domain decomposition methods for second-order linear quadratic optimal control problems.
300 $a 201 p.
500 $a Source: Masters Abstracts International, Volume: 42-05, page: 1725.
500 $a Chair: Matthias Heinkenschloss.
502 $a Thesis (M.A.)--Rice University, 2004.
520 $a Optimal control problems governed by time-dependent differential equations lead to large scale problems. Their numerical solution is challenging due to large storage demands resulting from the coupling in time of the solution of the governing (state) equation and the so-called adjoint equation.
520 $a This thesis investigates two time-domain decomposition based methods for the solution of linear quadratic control problems governed by second order differential equations. Both methods deal with storage requirements by reformulating the problem so that some of the variables at time subdomains are expressed as implicit functions of others; through the solution of a local state equation or control subproblem. The methods differ in the variables that are being eliminated and, more importantly, in the transmission conditions that link the subproblems at time interfaces. This work exposes the connections between formulations, extends algorithmic approaches for the second formulation, and compares numerically the performance of each method.
590 $a School code: 0187.
650 4 $a Mathematics. $3 146772
690 $a 0405
710 2 0 $a Rice University. $3 1000005713
773 0 $t Masters Abstracts International $g 42-05.
790 1 0 $a Heinkenschloss, Matthias, $e advisor
790 $a 0187
791 $a M.A.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1419065 $z Download fulltext (下載全文)

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