A global optimization approach to fractional optimal control

In this paper, we consider a fractional optimal control problem governed by system of linear differential equations, where its cost function is expressed as the ratio of convex and concave functions. The problem is a hard nonconvex optimal control problem and application of Pontriyagin's princi...

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Main Authors: Rentsen, E., Zhou, Jingyang, Teo, Kok Lay
Format: Journal Article
Published: American Institute of Mathematical Sciences 2016
Online Access:http://hdl.handle.net/20.500.11937/32410
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author Rentsen, E.
Zhou, Jingyang
Teo, Kok Lay
author_facet Rentsen, E.
Zhou, Jingyang
Teo, Kok Lay
author_sort Rentsen, E.
building Curtin Institutional Repository
collection Online Access
description In this paper, we consider a fractional optimal control problem governed by system of linear differential equations, where its cost function is expressed as the ratio of convex and concave functions. The problem is a hard nonconvex optimal control problem and application of Pontriyagin's principle does not always guarantee finding a global optimal control. Even this type of problems in a finite dimensional space is known as NP hard. This optimal control problem can, in principle, be solved by Dinkhelbach algorithm [10]. However, it leads to solving a sequence of hard D.C programming problems in its finite dimensional analogy. To overcome this difficulty, we introduce a reachable set for the linear system. In this way, the problem is reduced to a quasiconvex maximization problem in a finite dimensional space. Based on a global optimality condition, we propose an algorithm for solving this fractional optimal control problem and we show that the algorithm generates a sequence of local optimal controls with improved cost values. The proposed algorithm is then applied to several test problems, where the global optimal cost value is obtained for each case.
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spelling curtin-20.500.11937-324102019-02-19T05:35:39Z A global optimization approach to fractional optimal control Rentsen, E. Zhou, Jingyang Teo, Kok Lay In this paper, we consider a fractional optimal control problem governed by system of linear differential equations, where its cost function is expressed as the ratio of convex and concave functions. The problem is a hard nonconvex optimal control problem and application of Pontriyagin's principle does not always guarantee finding a global optimal control. Even this type of problems in a finite dimensional space is known as NP hard. This optimal control problem can, in principle, be solved by Dinkhelbach algorithm [10]. However, it leads to solving a sequence of hard D.C programming problems in its finite dimensional analogy. To overcome this difficulty, we introduce a reachable set for the linear system. In this way, the problem is reduced to a quasiconvex maximization problem in a finite dimensional space. Based on a global optimality condition, we propose an algorithm for solving this fractional optimal control problem and we show that the algorithm generates a sequence of local optimal controls with improved cost values. The proposed algorithm is then applied to several test problems, where the global optimal cost value is obtained for each case. 2016 Journal Article http://hdl.handle.net/20.500.11937/32410 10.3934/jimo.2016.12.73 American Institute of Mathematical Sciences fulltext
spellingShingle Rentsen, E.
Zhou, Jingyang
Teo, Kok Lay
A global optimization approach to fractional optimal control
title A global optimization approach to fractional optimal control
title_full A global optimization approach to fractional optimal control
title_fullStr A global optimization approach to fractional optimal control
title_full_unstemmed A global optimization approach to fractional optimal control
title_short A global optimization approach to fractional optimal control
title_sort global optimization approach to fractional optimal control
url http://hdl.handle.net/20.500.11937/32410