Extension technology and extrema selections in a stochastic multistart algorithm for optimal control problems

Alexander Yu. Gornov (), Tatiana S. Zarodnyuk, Anton S. Anikin and Evgeniya A. Finkelstein
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Alexander Yu. Gornov: Matrosov Institute for Systems Dynamics and Control Theory of SB RAS
Tatiana S. Zarodnyuk: Matrosov Institute for Systems Dynamics and Control Theory of SB RAS
Anton S. Anikin: Matrosov Institute for Systems Dynamics and Control Theory of SB RAS
Evgeniya A. Finkelstein: Matrosov Institute for Systems Dynamics and Control Theory of SB RAS

Journal of Global Optimization, 2020, vol. 76, issue 3, No 7, 533-543

Abstract: Abstract The paper proposes a method for finding the minimum value of a functional in nonlinear nonconvex optimal control problems. The method takes advantage of the hidden convexity property of the controlled differential equations systems. Application of the multistart idea with extrema selection procedures makes it possible to create software that does not strongly depend on the problem size and supplies additional information about the object under investigation. Three test problems are considered to show specific properties of using the stochastic multistart algorithm and extension numerical technology.

Keywords: Optimal control; Hidden convexity; Global extremum; Nonlinear system (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10898-019-00821-x

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