Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Advances in Computer, Signals and Systems
  4. Vol 6, Issue 3, 2022

Path Tracking Control of Patrol Unmanned Vehicle Based on GWO-PID

Download as PDF

DOI: 10.23977/acss.2022.060312 | Downloads: 15 | Views: 725

Author(s)

Jinlong Zheng 1, Meng Li 1

Affiliation(s)

1 School of Electrical Engineering, University of Jinan, Jinan, 250000, China

Corresponding Author

Jinlong Zheng

ABSTRACT

Aiming at the problems that the traditional PID control parameters are complex to set and it is difficult to find the optimal parameters, which affects the accuracy and stability of the path tracking control of patrol unmanned vehicles, a GWO-PID path tracking control system is designed by combining gray wolf optimization algorithm with PID control algorithm. In this paper, the kinematic model of patrol unmanned vehicle is established at first, and the corresponding simulation model is designed in MATLAB. The front wheel angle is controlled by PID controller to realize the path tracking of the unmanned vehicle; Then gray wolf optimization algorithm is used to optimize the parameters of PID control, and the optimized parameters are simulated. The results show that the optimized PID controller has better control effect; Finally, the actual path tracking test is carried out with reference to the optimized parameters, and the test effect is good.

KEYWORDS

Gray Wolf Optimization Algorithm, Path Tracking, Patrol Unmanned Vehicle

CITE THIS PAPER

Jinlong Zheng, Meng Li, Path Tracking Control of Patrol Unmanned Vehicle Based on GWO-PID. Advances in Computer, Signals and Systems (2022) Vol. 6: 102-109. DOI: http://dx.doi.org/10.23977/acss.2022.060312.

REFERENCES

[1] Hans P. Moravec. (1990) The Stanford Cart and the CMU Rover. Autonomous Robot Vehicles, Springer, 407-419. 
[2] Anh-Tu Nguyen, Chouk i Sentouh, Jean-Christophe Popieul. Fuzzy steering control for autonomous vehicles under actuator saturation. Journal of the Franklin Institute, 2017, 335(18): 9374-9395.
[3] Yang Chen, Jiang Xin, et al. (2022) Path following control of PID controller parameters optimized by genetic algorithm. Manufacturing Automation, 44, 5, 78-81. 
[4] Wang Xindong, Xu Yanlei, et al. (2020) Research on Variable Spraying System Based on Grey Wolf Optimized PID Control. Journal of Agricultural Mechanization Research, 42, 5, 114-119.
[5] Liu Zhiqun, Shang Huilin. (2021) Optimization of PID Control Parameters of Overhead Crane Based on Grey Wolf Optimizer. Journal of Technology, 21, 2, 167-171. 
[6] Xu Yang, Lu Liping, et al. (2019) Unified Modeling of Trajectory Planning and Tracking for Unmanned Vehicle. Acta Automatica Sinica, 45, 4, 799-807.
[7] Mirjalili S, Mirjalili SM, Lewis A. (2014) Grey wolf optimizer. Advances in Engineering Software, 69, 46-61. 
[8] Liu Wei, Guo Zhiqing, et al. (2022) Improved grey wolf optimizer based on cooperative attack strategy and its PID parameter optimization. Journal of Frontiers of Computer Science and Technology, 7, 1-16.

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 15978
Visits: 270925

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.