The University of Southampton
University of Southampton Institutional Repository

General approach for solving optimal control problems using optimization techniques

General approach for solving optimal control problems using optimization techniques
General approach for solving optimal control problems using optimization techniques
A general approach to the determination of approximate solutions of general control problems by exploiting modern global search and optimization techniques is proposed. According to the methodology developed in this paper, controls are represented by discrete vectors and substituted in system equations. The components of these vectors are regarded as variables of a performance index based goal function that is to be minimized with respect to the system constraints. Such an approach enables modeling and solution of a wide class of optimal control problems, arising in engineering practice, within a unified framework of constrained optimization techniques, including implementation of genetic algorithms for global optimization and multiobjective control. Computer realizations of the proposed method are mainly based on MATLAB simulation programs. The results obtained can be implemented to solve optimal control problems in the field of Computer Aided Control Engineering, Computer Integrated Manufacturing, Mechatronics and Robotics.
4503-4508
Dakev, N.V.
f91c4332-e605-43b6-964a-14efb5ec4248
Chipperfield, A.J.
524269cd-5f30-4356-92d4-891c14c09340
Fleming, P.J.
cb08bfe3-1947-44c6-937c-eba5e2033796
Dakev, N.V.
f91c4332-e605-43b6-964a-14efb5ec4248
Chipperfield, A.J.
524269cd-5f30-4356-92d4-891c14c09340
Fleming, P.J.
cb08bfe3-1947-44c6-937c-eba5e2033796

Dakev, N.V., Chipperfield, A.J. and Fleming, P.J. (1995) General approach for solving optimal control problems using optimization techniques. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. pp. 4503-4508 .

Record type: Conference or Workshop Item (Paper)

Abstract

A general approach to the determination of approximate solutions of general control problems by exploiting modern global search and optimization techniques is proposed. According to the methodology developed in this paper, controls are represented by discrete vectors and substituted in system equations. The components of these vectors are regarded as variables of a performance index based goal function that is to be minimized with respect to the system constraints. Such an approach enables modeling and solution of a wide class of optimal control problems, arising in engineering practice, within a unified framework of constrained optimization techniques, including implementation of genetic algorithms for global optimization and multiobjective control. Computer realizations of the proposed method are mainly based on MATLAB simulation programs. The results obtained can be implemented to solve optimal control problems in the field of Computer Aided Control Engineering, Computer Integrated Manufacturing, Mechatronics and Robotics.

This record has no associated files available for download.

More information

Published date: 25 October 1995

Identifiers

Local EPrints ID: 470266
URI: http://eprints.soton.ac.uk/id/eprint/470266
PURE UUID: b47d13ad-d80e-48d4-8098-cd2915e711ac
ORCID for A.J. Chipperfield: ORCID iD orcid.org/0000-0002-3026-9890

Catalogue record

Date deposited: 05 Oct 2022 16:39
Last modified: 23 Feb 2023 02:45

Export record

Contributors

Author: N.V. Dakev
Author: P.J. Fleming

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×