Autonomous racing using Linear Parameter Varying-Model Predictive Control (LPV-MPC)

This article presents an innovative control approach for autonomous racing vehicles. Linear Parameter Varying (LPV) theory is used to model the dynamics of the vehicle and implement an LPV-Model Predictive Controller (LPV-MPC) that can be computed online with reduced computational cost. The optimal...

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Detalles Bibliográficos
Autores: Alcalá Baselga, Eugenio|||0000-0002-6023-0014, Puig Cayuela, Vicenç|||0000-0002-6364-6429, Quevedo Casín, Joseba Jokin|||0000-0002-7827-2896, Rosolia, Ugo
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/340478
Acceso en línea:https://hdl.handle.net/2117/340478
https://dx.doi.org/10.1016/j.conengprac.2019.104270
Access Level:acceso abierto
Palabra clave:Predictive control
Autonomous vehicles
Automatic control
Control predictiu
Vehicles autònoms
Control automàtic
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
Descripción
Sumario:This article presents an innovative control approach for autonomous racing vehicles. Linear Parameter Varying (LPV) theory is used to model the dynamics of the vehicle and implement an LPV-Model Predictive Controller (LPV-MPC) that can be computed online with reduced computational cost. The optimal time problem is solved by an optimal off-line trajectory planner that calculates the best trajectory under the constraints of the circuit. An identification of the system model based on optimization is also carried out. The planning and control scheme is validated in simulation and experimentally in a real platform where the effectiveness of the proposed LPV-MPC is demonstrated.