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Paper WeB2.1

Righetti, Giovanni (Università di Padova), SASSELLA, ANDREA (Politecnico di MIlano), Lenzo, Basilio (University of Padua)

A Gradient Descent-Based Vehicle Optimizator for Enhanced State Estimation

Scheduled for presentation during the Regular Session "Vehicle dynamics " (WeB2), Wednesday, June 18, 2025, 14:00−14:20, Jos

AAC 2025 11th IFAC International Symposium on Advances in Automotive Control, June 15-18, 2025, Eindhoven, Netherlands

This information is tentative and subject to change. Compiled on June 1, 2025

Keywords Vehicle dynamics, control and state estimation

Abstract

Accurate vehicle state estimation is crucial for enhancing safety in modern automotive control systems. This paper presents a gradient descent-based algorithm designed to optimise the parameters of a 5-degree-of-freedom (DOFs) vehicle model for improved state estimation and control application. The algorithm is validated through simulations and experimental tests, demonstrating its ability to adjust vehicle parameters effectively and force the model to mimic the behaviour of the reference vehicle, reducing errors in key dynamics such as vehicle velocity and yaw rate.

 

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