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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2013, Volume 53, Number 12, Pages 2014–2028
DOI: https://doi.org/10.7868/S0044466913120077 (Mi zvmmf9959) 		 
This article is cited in 10 scientific papers (total in 10 papers)

Numerical methods for solving applied optimal control problems

A. Yu. Gornov, A. I. Tyatyushkin, E. A. Finkelshtein

Institute of System Dynamics and Control Theory, Siberian Branch, Russian Academy of Sciences, ul. Lermontova 134, Irkutsk, 664033, Russia
Full-text PDF (259 kB) Citations (10)
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DOI: https://doi.org/10.7868/S0044466913120077
Abstract: For an optimal control problem with state constraints, an iterative solution method is described based on reduction to a finite-dimensional problem, followed by applying a successive linearization algorithm with the use of an augmented Lagrangian. The efficiency of taking into account state constraints in optimal control computation is illustrated by numerically solving several application problems.
Key words: optimal control, state constraints, augmented Lagrangian, successive linearization, iteration methods.
Received: 27.12.2013
English version:
Computational Mathematics and Mathematical Physics, 2013, Volume 53, Issue 12, Pages 1825–1838
DOI: https://doi.org/10.1134/S0965542513120063
Bibliographic databases:
Document Type: Article
UDC: 519.626
Language: Russian
Citation: A. Yu. Gornov, A. I. Tyatyushkin, E. A. Finkelshtein, “Numerical methods for solving applied optimal control problems”, Zh. Vychisl. Mat. Mat. Fiz., 53:12 (2013), 2014–2028; Comput. Math. Math. Phys., 53:12 (2013), 1825–1838
Citation in format AMSBIB
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    • This publication is cited in the following 10 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Журнал вычислительной математики и математической физики Computational Mathematics and Mathematical Physics
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