LQR Optimal Control of Four-steering Vehicle Based on Particle Swarm Optimization Algorithm

Conference paper (2022)

Authors

Songfeng Zhu Beijing Institute of Technology
Xueyuan Li Beijing Institute of Technology
Xinyi Qu Inner Mongolia First Machinery Group
Qi Liu Beijing Institute of Technology
Z. Li Transport and Planning - CEG , Beijing Institute of Technology
Research Group
Transport and Planning (CEG) (TU Delft)
Copyright: © 2022 Songfeng Zhu, Xueyuan Li, Xinyi Qu, Qi Liu, Z. Li
DOI
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https://doi.org/10.1145/3548608.3559298
Particle swarm optimization LQR Fuzzy controller Side slip angle
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Published Date

2022

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Transport and Planning

Research Group

Transport and Planning

Abstract

This paper proposes a linear quadratic controller based on particle swarm algorithm for the rear wheel control of four-wheel steering vehicle. Particle swarm optimization with fitness functions is used to optimize the coefficients of the weight matrix offline. The fuzzy rules following the controller is used if the road condition is terrible. The simulation results show that the LQR control model based on particle swarm optimization makes the trajectory tracking of the vehicle better and the side slip angle of the vehicle lower. It can be proved that the controller has positive effect on handling stability of the vehicle and safety of drivers.