Motor control technology based on integrated meta-heuristic algorithm optimizer
This document addresses the speed-torque problem in motor control technology by proposing an optimizer based on a comprehensive meta-heuristic algorithm. This optimizer effectively mitigates the issue of heuristic optimization algorithms frequently becoming trapped in local optima. By monitoring the state of the "active particles," it provides real-time insights into the optimization process of the meta-heuristic algorithm. Additionally, the presence of the "active particle archive" facilitates the exploration of new optimization landscapes. The incorporation of other heuristic algorithms enables quicker and more accurate identification of suitable solutions. Furthermore, comprehensive performance evaluations using relevant motor model test functions have validated the feasibility of the optimizer. Ultimately, the results demonstrate that the optimizer significantly enhances the adjustment of control parameters for motors, leading to superior control outcomes.
Authors
- Wei Wu (ORCID: https://orcid.org/0000-0002-8734-1582)
- Du Shaoqing
- Geng Jialong
Institutions
- Shenyang University of Technology (CN)
Publication Details
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1109/ei264398.2024.10991749
- Primary Topic
- Advanced Decision-Making Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00