Towards intelligent control via genetic programming
Marchetti, Francesco and Minisci, Edmondo and Riccardi, Annalisa; (2020) Towards intelligent control via genetic programming. In: 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, GBR. ISBN 9781728169279 (https://doi.org/10.1109/IJCNN48605.2020.9207694)
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Abstract
In this paper an initial approach to Intelligent Control (IC) using Genetic Programming (GP) for access to space applications is presented. GP can be employed successfully to design a controller even for complex systems, where classical controllers fail because of the high nonlinearity of the systems. The main property of GP, that is its ability to autonomously create explicit mathematical equations starting from a very poor knowledge of the considered plant, or just data, can be exploited for a vast range of applications. Here, GP has been used to design the control law in an Intelligent Control framework for a modified version of the Goddard Rocket problem in 3 different failure scenarios, where the approach to IC consists in an online re-evaluation of the control law using GP when a considerably big change in the environment or in the plant happens. The presented results are then used to highlight the potential benefits of the method, as well as aspects that will need further developments.
ORCID iDs
Marchetti, Francesco ORCID: https://orcid.org/0000-0003-4552-0467, Minisci, Edmondo ORCID: https://orcid.org/0000-0001-9951-8528 and Riccardi, Annalisa ORCID: https://orcid.org/0000-0001-5305-9450;-
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Item type: Book Section ID code: 73537 Dates: DateEvent28 September 2020Published20 July 2020Published Online15 March 2020AcceptedNotes: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Mechanical engineering and machinery Department: Faculty of Engineering > Mechanical and Aerospace Engineering Depositing user: Pure Administrator Date deposited: 11 Aug 2020 13:08 Last modified: 11 Nov 2024 15:23 URI: https://strathprints.strath.ac.uk/id/eprint/73537