MPC Path Tracking Control Based on GA-PAO

Farong Kou; Jie Ren

doi:10.54097/9jszvh12

Authors

Farong Kou
Jie Ren

DOI:

https://doi.org/10.54097/9jszvh12

Keywords:

Path Tracking; MPC; Dynamical Model; GA-PSO.

Abstract

In order to improve the path tracking performance and stability of driverless vehicles. In this paper, a path tracking control strategy based on MPC is proposed to establish a three-degree-of-freedom vehicle dynamical model as a reference model, design the MPC controller, determine the objective function and add constraints. Optimization of important time-domain parameters of model predictive controllers by improved GA-PSO. A Carsim/Simulink co-simulation platform was built to simulate the controller under double-shifted line conditions to verify its effectiveness. Simulation results show that the tracking performance and stability of the optimized MPC controller are much better.

Downloads

Download data is not yet available.

References

[1] Zhang Yujin. Research and Prospect of unmanned driving technology under the background of Artificial Intelligence [J]. Digital Communications World,2018(2):1-2.

[2] Chen Huiyan, Chen Shuping, Gong Jianwei. Research review on lateral control methods of intelligent vehicles [J]. Journal of Military Engineering, 2017, 38( 6) : 1203 - 1214.

[3] Al-Mayyahi A, Wang W, Birch P. Path tracking of autonomous ground vehicle based on fractional order PID controller optimized by PSO[C]//2015 IEEE 13th International Symposium on Applied Machine Intelligence and Informatics (SAMI). IEEE, 2015: 109-114.

[4] LIU J, YANG C. Adaptive Path Tracking Controller forIntelligent Driving Vehicles for Large Curvature Paths[J].SAE International Journal of Connected and AutomatedVehicles, 2022, 6(2): 199-219.

[5] ZHOU B, SU X, YU H, et al. Research on path tracking of articulated steering tractor based on modified model predictive control[J]. Agriculture, 2023, 13(4): 871.

[6] Hu Minmin, Wei Xinhua, Wang Aichen, et al. Path tracking control method of tractor based on adaptive MPC[J]. Research on Agricultural Mechanization, 2024, 46(6):227-233.

[7] Dong Na, Chen Zengqiang, Sun Qinglin, et al. Constrained model predictive controller based on particle swarm optimization. Control Theory and Applications, 2009, 26(09): 965-969.

[8] Feng, Wang Hui, Yu Lei, et al. Matlab intelligent algorithm 30 case analysis [M]. Beijing: Beijing University of Aeronautics and Astronautics, 2011.

[9] Falcone P. Nonlinear model predictive control for autonomous vehicles. Benevento: University of Sannio, 2007.

[10] Gong Jianwei, Jiang Yan, Xu Wei. Autonomous vehicle model predictive control [M]. Beijing: Beijing Institute of Technology, 2014.