Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation.
To address the susceptibility of conventional vector control systems for permanent magnet synchronous motors (PMSMs) to motor parameter variations and load disturbances, a novel control method combining an improved Grasshopper Optimization Algorithm (GOA) with a variable universe fuzzy Proportional-...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0318094 |
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| author | Taochang Li Ang Li Limin Hou |
| author_facet | Taochang Li Ang Li Limin Hou |
| author_sort | Taochang Li |
| collection | DOAJ |
| description | To address the susceptibility of conventional vector control systems for permanent magnet synchronous motors (PMSMs) to motor parameter variations and load disturbances, a novel control method combining an improved Grasshopper Optimization Algorithm (GOA) with a variable universe fuzzy Proportional-Integral (PI) controller is proposed, building upon standard fuzzy PI control. First, the diversity of the population and the global exploration capability of the algorithm are enhanced through the integration of the Cauchy mutation strategy and uniform distribution strategy. Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima. The improved GOA is then employed to optimize the contraction-expansion factor of the variable universe fuzzy PI controller, achieving enhanced control performance for PMSMs. Additionally, to address the high torque and current ripple issues commonly associated with traditional PI controllers in the current loop, Model Predictive Control (MPC) is adopted to further improve control performance. Finally, experimental results validate the effectiveness of the proposed control scheme, demonstrating precise motor speed control, rapid and stable current tracking, as well as improved system robustness. |
| format | Article |
| id | doaj-art-5f585b017ce548968b827501a6fc5852 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-5f585b017ce548968b827501a6fc58522025-02-05T05:31:42ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031809410.1371/journal.pone.0318094Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation.Taochang LiAng LiLimin HouTo address the susceptibility of conventional vector control systems for permanent magnet synchronous motors (PMSMs) to motor parameter variations and load disturbances, a novel control method combining an improved Grasshopper Optimization Algorithm (GOA) with a variable universe fuzzy Proportional-Integral (PI) controller is proposed, building upon standard fuzzy PI control. First, the diversity of the population and the global exploration capability of the algorithm are enhanced through the integration of the Cauchy mutation strategy and uniform distribution strategy. Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima. The improved GOA is then employed to optimize the contraction-expansion factor of the variable universe fuzzy PI controller, achieving enhanced control performance for PMSMs. Additionally, to address the high torque and current ripple issues commonly associated with traditional PI controllers in the current loop, Model Predictive Control (MPC) is adopted to further improve control performance. Finally, experimental results validate the effectiveness of the proposed control scheme, demonstrating precise motor speed control, rapid and stable current tracking, as well as improved system robustness.https://doi.org/10.1371/journal.pone.0318094 |
| spellingShingle | Taochang Li Ang Li Limin Hou Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation. PLoS ONE |
| title | Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation. |
| title_full | Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation. |
| title_fullStr | Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation. |
| title_full_unstemmed | Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation. |
| title_short | Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation. |
| title_sort | improved goa based fuzzy pi speed control of pmsm with predictive current regulation |
| url | https://doi.org/10.1371/journal.pone.0318094 |
| work_keys_str_mv | AT taochangli improvedgoabasedfuzzypispeedcontrolofpmsmwithpredictivecurrentregulation AT angli improvedgoabasedfuzzypispeedcontrolofpmsmwithpredictivecurrentregulation AT liminhou improvedgoabasedfuzzypispeedcontrolofpmsmwithpredictivecurrentregulation |