Genetic Programming Guidance Control System for a Reentry Vehicle under Uncertainties

Created by W.Langdon from gp-bibliography.bib Revision:1.7764

@Article{Marchetti:2021:math,

• author = "Francesco Marchetti and Edmondo Minisci",
• title = "Genetic Programming Guidance Control System for a Reentry Vehicle under Uncertainties",
• journal = "Mathematics",
• year = "2021",
• volume = "9",
• number = "16",
• article-number = "1868",
• month = "6 " # aug,
• keywords = "genetic algorithms, genetic programming, IGP, FESTIP-FSS5 RLV, evolutionary optimization, space vehicle, control, differential evolution, reusable launch vehicle",
• ISSN = "2227-7390",
• publisher = "MDPI",
• URL = "https://www.mdpi.com/2227-7390/9/16/1868",
• DOI = "doi:10.3390/math9161868",
• size = "19 pages",
• abstract = "As technology improves, the complexity of controlled systems increases as well. Alongside it, these systems need to face new challenges, which are made available by this technology advancement. To overcome these challenges, the incorporation of AI into control systems is changing its status, from being just an experiment made in academia, towards a necessity. Several methods to perform this integration of AI into control systems have been considered in the past. In this work, an approach involving GP to produce, offline, a control law for a reentry vehicle in the presence of uncertainties on the environment and plant models is studied, implemented and tested. The results show the robustness of the proposed approach, which is capable of producing a control law of a complex nonlinear system in the presence of big uncertainties. This research aims to describe and analyze the effectiveness of a control approach to generate a nonlinear control law for a highly nonlinear system in an automated way. Such an approach would benefit the control practitioners by providing an alternative to classical control approaches, without having to rely on linearisation techniques.",
• notes = "Also known as \cite{math9161868}. Intelligent Computational Engineering Laboratory (ICE-Lab), University of Strathclyde, Glasgow G11XJ, UK",

}

Genetic Programming entries for Francesco Marchetti Edmondo Minisci

Citations