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Optimized adaptive MPC for lateral control of autonomous vehicles

Yassine Kebbati, Vicenç Puig, Naima Ait-Oufroukh, Vincent Vigneron, Dalil Ichalal

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Abstract

Autonomous vehicles are the upcoming solution to most transportation problems such as safety, comfort and efficiency. The steering control is one of the main important tasks in achieving autonomous driving. Model predictive control (MPC) is among the fittest controllers for this task due to its optimal performance and ability to handle constraints. This paper proposes an adaptive MPC controller (AMPC) for the path tracking task, and an improved PSO algorithm for optimising the AMPC parameters. Parameter adaption is realised online using a lookup table approach. The propose AMPC performance is assessed and compared with the classic MPC and the Pure Pursuit controller through simulations.

Topics & Concepts

Model predictive controlTask (project management)Controller (irrigation)Computer scienceControl theory (sociology)Lookup tableTable (database)Path (computing)Adaptive controlTracking (education)Control (management)Control engineeringEngineeringArtificial intelligenceAgronomyData miningBiologySystems engineeringProgramming languagePedagogyPsychologyAdvanced Control Systems OptimizationVehicle Dynamics and Control SystemsRobotic Path Planning Algorithms
Optimized adaptive MPC for lateral control of autonomous vehicles | Litcius