Multi-Objective Optimization of a Path-following MPC for Vehicle\n Guidance: A Bayesian Optimization Approach

2021/04/08 by Ali Gharib, Gharib, Ali, David A. Stenger +5 · 3 citations
Engineering · #Advanced Control Systems Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #Real-time simulation and control systems #Robotics (cs.RO) #Systems and Control (eess.SY) #Vehicle Dynamics and Control Systems #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2104.03773

openalex publication_date 2021/04/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper tackles the multi-objective optimization of the cost functional of\na path-following model predictive control for vehicle longitudinal and lateral\ncontrol. While the inherent optimal character of the model predictive control\nand the direct consideration of constraints gives a very powerful tool for many\napplications, is the determination of an appropriate cost functional a\nnon-trivial task. This results on the one hand from the number of degrees of\nfreedom or the multitude of adjustable parameters and on the other hand from\nthe coupling of these. To overcome this situation a Bayesian optimization\nprocedure is present, which gives the possibility to determine optimal cost\nfunctional parameters for a given desire. Moreover, a Pareto-front for a whole\nset of possible configurations can be computed.\n

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