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

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

Zhu, Songfeng (Beijing Institute of Technology)
Li, Xueyuan (Beijing Institute of Technology)
Qu, Xinyi (Inner Mongolia First Machinery Group)
Liu, Qi (Beijing Institute of Technology)
Li, Z. (TU Delft Transport and Planning; Beijing Institute of Technology)

2022

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.

fuzzy controller
LQR
particle swarm optimization
side slip angle

http://resolver.tudelft.nl/uuid:1dec8ae3-f12e-4cfe-b3b0-5932eb39f2ed

https://doi.org/10.1145/3548608.3559298

Association for Computing Machinery (ACM)

2023-07-01

9781450397179

Proceedings of 2022 2nd International Conference on Control and Intelligent Robotics, ICCIR 2022

2nd International Conference on Control and Intelligent Robotics, ICCIR 2022, 2022-06-24 → 2022-06-26, Virtual, Online, China

ACM International Conference Proceeding Series

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2022 Songfeng Zhu, Xueyuan Li, Xinyi Qu, Qi Liu, Z. Li