An anti-swing control method for crane robot with liquid container lifting

The sloshing of liquid in containers being lifted by crane robots presents a serious safety hazard. To effectively suppress liquid sloshing during the lifting process, a sliding mode control method is proposed in this paper. An equivalent dynamic model of the crane robot lifting liquid containers is developed based on a mass-spring system. A sliding mode surface is constructed that incorporates the coupling of trolley displacement, payload swing angle, and liquid sloshing displacement. The sliding mode control law is derived, and the stability of the closed-loop system is analyzed. The simulation results have demonstrated the effectiveness and robustness of the proposed control method.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/ricai64321.2024.10911553
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

An anti-swing control method for crane robot with liquid container lifting

Guolong Chen, Qian Lin, Wuyin Jin, Shourui Wang
Robotic Path Planning Algorithms
article

An anti-swing control method for crane robot with liquid container lifting

Guolong Chen, Qian Lin, Wuyin Jin, Shourui Wang
article en

Abstract

The sloshing of liquid in containers being lifted by crane robots presents a serious safety hazard. To effectively suppress liquid sloshing during the lifting process, a sliding mode control method is proposed in this paper. An equivalent dynamic model of the crane robot lifting liquid containers is developed based on a mass-spring system. A sliding mode surface is constructed that incorporates the coupling of trolley displacement, payload swing angle, and liquid sloshing displacement. The sliding mode control law is derived, and the stability of the closed-loop system is analyzed. The simulation results have demonstrated the effectiveness and robustness of the proposed control method.

Lanzhou University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 72%
Robotic Path Planning Algorithms
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