Abstract
One of the main challenges of the overhead cranes is accurate positioning of payloads due to the swing angle, which compromizes environmental safety. This paper applies an Integral Linear Quadratic Regulator (I-LQR) to provide optimal control for a 3D overhead crane. The weighting matrices of the LQR are tuned using the Differential Evolution Optimization (DEO) algorithm. Resulting in an enhanced crane performance with zero overshoot and 85% reduction of the settling time compared to conventionally tuned LQR. Further, this work adapts the Dynamic Window Approach (DWA), a local path planning algorithm, to guide the crane in navigating complex environments and safely delivering weights to the target point. The results highlight the performance of the optimized crane in tracking the trajectory provided by the crane-modified DWA algorithm.
| Original language | English |
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| Title of host publication | ICAC 2025 - 30th International Conference on Automation and Computing |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331525453 |
| DOIs | |
| State | Published - 2025 |
| Event | 30th International Conference on Automation and Computing, ICAC 2025 - Loughborough, United Kingdom Duration: 27 Aug 2025 → 29 Aug 2025 |
Publication series
| Name | ICAC 2025 - 30th International Conference on Automation and Computing |
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Conference
| Conference | 30th International Conference on Automation and Computing, ICAC 2025 |
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| Country/Territory | United Kingdom |
| City | Loughborough |
| Period | 27/08/25 → 29/08/25 |
Bibliographical note
Publisher Copyright:© 2025 IEEE.
Keywords
- 3D overhead crane
- Differential Evolution Optimization
- DWA
- Integral LQR
- path planning
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Modeling and Simulation
- Industrial and Manufacturing Engineering
- Control and Optimization