Research on unmanned electric shovel autonomous driving path tracking control based on improved pure tracking and fuzzy control

This paper proposes a path tracking control method combining pure tracking algorithms and self‐adaptive fuzzy control for autonomous driving of an unmanned electric shovel. An improved pure tracking controller was designed based on the kinematic model of heavy crawler taking both the value of deviat...

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Bibliographic Details
Published inJournal of field robotics Vol. 40; no. 7; pp. 1739 - 1753
Main Authors Wu, Guohua, Wang, Guoqiang, Bi, Qiushi, Wang, Yongpeng, Fang, Yi, Guo, Guangyong, Qu, Wentao
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc 01.10.2023
Subjects
Adaptive algorithms
Adaptive control
Control methods
Control systems design
Controllers
Fuzzy control
Kinematics
Path tracking
pure tracking
Tracking control
unmanned electric shovel
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Summary:This paper proposes a path tracking control method combining pure tracking algorithms and self‐adaptive fuzzy control for autonomous driving of an unmanned electric shovel. An improved pure tracking controller was designed based on the kinematic model of heavy crawler taking both the value of deviation and its variation as inputs with the crawler speed on each side as output. The proposed controller and MPC algorithm were simulated using MATLAB for comparison. The results show that the proposed controller has more anthropomorphic characteristics than the MPC method. To verify the actual control effect of the controller, experiments were carried out using a prototype electric shovel for different working conditions. The experimental results proved that the controller is able to meet the control requirements for unmanned electric shovel path tracking.
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ISSN:1556-4959
1556-4967
DOI:10.1002/rob.22208