Towards intelligent control via genetic programming

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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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.
Original languageEnglish
Title of host publication2020 International Joint Conference on Neural Networks (IJCNN)
Place of PublicationPiscataway, NJ.
PublisherIEEE
Number of pages8
ISBN (Print)9781728169279
DOIs
Publication statusPublished - 28 Sep 2020
EventIEEE World Congress on Computational Intelligence 2020 - Glasgow, United Kingdom
Duration: 19 Jul 202024 Jul 2020
https://wcci2020.org/

Conference

ConferenceIEEE World Congress on Computational Intelligence 2020
Abbreviated titleWCCI
Country/TerritoryUnited Kingdom
CityGlasgow
Period19/07/2024/07/20
Internet address

Keywords

  • genetic programming
  • intelligent control
  • machine learning
  • evolutionary algorithm
  • access to space

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