Robust path-following control design of heavy vehicles based on multiobjective evolutionary optimization

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorMorais, Gustavo A. Prudencio de-
Autor(es): dc.creatorMarcos, Lucas Barbosa-
Autor(es): dc.creatorBarbosa, Filipe Marques-
Autor(es): dc.creatorBarbosa, Bruno H. G.-
Autor(es): dc.creatorTerra, Marco Henrique-
Autor(es): dc.creatorGrassi Junior, Valdir-
Data de aceite: dc.date.accessioned2026-02-09T11:18:57Z-
Data de disponibilização: dc.date.available2026-02-09T11:18:57Z-
Data de envio: dc.date.issued2022-07-08-
Data de envio: dc.date.issued2022-07-08-
Data de envio: dc.date.issued2022-04-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/50537-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.eswa.2021.116304-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1138263-
Descrição: dc.descriptionThe ability to deal with systems parametric uncertainties is an essential issue for heavy self-driving vehicles in unconfined environments. In this sense, robust controllers prove to be efficient for autonomous navigation. However, uncertainty matrices for this class of systems are usually defined by algebraic methods which demand prior knowledge of the system dynamics. In this case, the control system designer depends on the quality of the uncertain model to obtain an optimal control performance. This work proposes a robust recursive controller designed via multiobjective optimization to overcome these shortcomings. Furthermore, a local search approach for multiobjective optimization problems is presented. The proposed method applies to any multiobjective evolutionary algorithm already established in the literature. The results presented show that this combination of model-based controller and machine learning improves the effectiveness of the system in terms of robustness, stability and smoothness.-
Idioma: dc.languageen-
Publicador: dc.publisherElsevier-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceExpert Systems with Applications-
Palavras-chave: dc.subjectAutonomous vehicles-
Palavras-chave: dc.subjectPath-following-
Palavras-chave: dc.subjectRobust control-
Palavras-chave: dc.subjectMultiobjective optimization-
Palavras-chave: dc.subjectEvolutionary algorithms-
Palavras-chave: dc.subjectVeículos autônomos-
Palavras-chave: dc.subjectSeguimento de trajetória-
Palavras-chave: dc.subjectControle robusto-
Palavras-chave: dc.subjectOtimização multiobjetivo-
Palavras-chave: dc.subjectAlgoritmos evolutivos-
Título: dc.titleRobust path-following control design of heavy vehicles based on multiobjective evolutionary optimization-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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