Description
This research summary outlines the advancements made over the past year in enhancing control strategies for Permanent Magnet Synchronous Motor (PMSM) drive systems. The focus has been on integrating metaheuristic algorithm tuning strategies within vector control frameworks, validated through a highly adaptable and modular PMSM experimental platform. A significant portion of this report delves into the comparative analysis of various control algorithms, including single-objective and multi-objective optimization approaches, to determine their suitability for PMSM drive systems.The study's findings demonstrate that multi-objective optimization algorithms, such as NSGA-II, are better suited for tuning the control parameters of PMSM systems compared to single-objective algorithms. This conclusion is drawn from the ability of multi-objective algorithms to analyze trade-offs among key performance indicators—such as rise time, overshoot, oscillation, and steady-state error—thereby achieving a more balanced and optimized control response.
Through experimental validation, it has been observed that the position feedback in systems tuned using NSGA-II exhibits significantly lower oscillation and reduced steady-state error compared to manually tuned PI controllers. However, the results also indicate areas for further improvement, particularly in enhancing the robustness of the NSGA-II algorithm to ensure stable dynamic responses under extreme conditions.
Future research will focus on refining these algorithms to achieve even more optimal control results and to enhance the robustness of the system, aiming to realize global optimization in PMSM drive systems.
| Period | 1 Jun 2023 → 1 Sept 2026 |
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| Degree of Recognition | National |