<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>As an important carrier of intelligent logistics, AGV can effectively reduce the labor cost of factories and warehouses. With the comprehensive promotion of “smart manufacturing”, the manufacturing industry has a stronger demand for automated AGV logistics systems. This paper firstly analyzes the principle of fuzzy PID controller and establishes its kinematic model to obtain the intrinsic relationship between the motion form and the speed of each driving wheel. Secondly, through the data measured and fed back by the fuzzy PID control system, the AGV driving angle deviation and position deviation are used as the input of the fuzzy controller; its fuzzy deviation correction technology is applied to realize the path correction of the AGV and ensure the stable operation of the AGV through the cooperative motion control technology. Finally, MATLAB software establishes the joint simulation model of the AGV fuzzy PID control system. The results show that through the two algorithms of PID control and fuzzy PID control correction test, the fuzzy PID controller system corrects the deflection efficiency by 47.41%; in the kinematic test, the path tracking efficiency is increased by 30.76%, the distance correction efficiency is increased by 69.56%, the angle correction efficiency is increased by 69.56%, and the average performance is increased by 53.44%. Through the two comparisons, it is concluded that the fuzzy controller designed in this paper has the advantages of fast response speed, good stability, and strong deflection correction performance, which substantially improves the speed and accuracy of intelligent search of intelligent vehicles.</p>
</abstract>

As an important carrier of intelligent logistics, AGV can effectively reduce the labor cost of factories and warehouses. With the comprehensive promotion of “smart manufacturing”, the manufacturing industry has a stronger demand for automated AGV logistics systems. This paper firstly analyzes the principle of fuzzy PID controller and establishes its kinematic model to obtain the intrinsic relationship between the motion form and the speed of each driving wheel. Secondly, through the data measured and fed back by the fuzzy PID control system, the AGV driving angle deviation and position deviation are used as the input of the fuzzy controller; its fuzzy deviation correction technology is applied to realize the path correction of the AGV and ensure the stable operation of the AGV through the cooperative motion control technology. Finally, MATLAB software establishes the joint simulation model of the AGV fuzzy PID control system. The results show that through the two algorithms of PID control and fuzzy PID control correction test, the fuzzy PID controller system corrects the deflection efficiency by 47.41%; in the kinematic test, the path tracking efficiency is increased by 30.76%, the distance correction efficiency is increased by 69.56%, the angle correction efficiency is increased by 69.56%, and the average performance is increased by 53.44%. Through the two comparisons, it is concluded that the fuzzy controller designed in this paper has the advantages of fast response speed, good stability, and strong deflection correction performance, which substantially improves the speed and accuracy of intelligent search of intelligent vehicles.

Research on AGV cart control system based on fuzzy PID control

Department of Mechanical and Electrical Engineering

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Research on AGV cart control system based on fuzzy PID control"}

As an important carrier of intelligent logistics, AGV can effectively reduce the labor cost of factories and warehouses. With the comprehensive promotion of...

Research on AGV cart control system based on fuzzy PID control

Online veröffentlicht: 02. Aug. 2023

Seitenbereich: -

Eingereicht: 27. Aug. 2022

Akzeptiert: 10. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00127

Schlüsselwörter
AGV, Intelligent logistics, Fuzzy PID control, Deviation, Fuzzy correction

© 2023 Yuanyuan Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on AGV cart control system based on fuzzy PID control

Online veröffentlicht: 02. Aug. 2023

Seitenbereich: -

Eingereicht: 27. Aug. 2022

Akzeptiert: 10. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00127

SchlüsselwörterAGV, Intelligent logistics, Fuzzy PID control, Deviation, Fuzzy correction

© 2023 Yuanyuan Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
AGV, Intelligent logistics, Fuzzy PID control, Deviation, Fuzzy correction