Longitudinal Control of an Autonomous Truck With Unobserved Gears

Autor(es)

Bueno, Jose Nuno A. D. ; Marcos, Lucas B. ; Rocha, Kaio D. T. ; Terra, Marco H. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 2021 IEEE URUCON; v. N/A, p. 4-pg., 2021-01-01.

Resumo

We provide a solution for the longitudinal control problem of heavy-duty vehicles when there is no information about the actual gear engaged by the automatic gearbox. The vehicle is modeled as a discrete-time Markov jump linear system based on a previous experimental identification procedure. The engaging of each gear corresponds to the operation modes in a Markov chain. We augment the longitudinal model, such that the information about the actual mode becomes an uncertain term. It is then possible to define an optimization problem whose solution yields a specific mode-independent regulator framework. Simulation results show that the obtained state feedback gain stabilizes the closed-loop system in spite of unobserved operation modes and adequately tracks the reference trajectories of states. (AU)

• Processo FAPESP: 17/16346-4 - Controle tolerante a falhas de rede de comunicação para o movimento coordenado de robôs heterogêneos
• Beneficiário: Kaio Douglas Teófilo Rocha
• Modalidade de apoio: Bolsas no Brasil - Doutorado Direto
• Processo FAPESP: 14/50851-0 - INCT 2014: Instituto Nacional de Ciência e Tecnologia para Sistemas Autônomos Cooperativos Aplicados em Segurança e Meio Ambiente
• Beneficiário: Marco Henrique Terra
• Modalidade de apoio: Auxílio à Pesquisa - Temático