Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller
Abstract A brushless DC (BLDC) motor is synchronous motor with trapezoidal/square wave counter-electromotive force, which is a typical example of highly coupled nonlinear systems. In industrial control, BLDC motor drive usually uses proportional–integral (PI) controller to control the speed, but it...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer
2022-10-01
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| Series: | SN Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-022-05179-6 |
| _version_ | 1828161321034579968 |
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| author | Jun Shi Qingtao Mi Weifeng Cao Lintao Zhou |
| author_facet | Jun Shi Qingtao Mi Weifeng Cao Lintao Zhou |
| author_sort | Jun Shi |
| collection | DOAJ |
| description | Abstract A brushless DC (BLDC) motor is synchronous motor with trapezoidal/square wave counter-electromotive force, which is a typical example of highly coupled nonlinear systems. In industrial control, BLDC motor drive usually uses proportional–integral (PI) controller to control the speed, but it is very difficult to adjust the scale factors. In this study, we present a particle swarm algorithm-tuned fuzzy logic-PI (PF-PI) controller applied to the speed control system. The objective of this paper is to optimally tune the PI controller parameters to obtain the best drive response. The scale factors are optimized using particle swarm optimized-PI (P-PI) controller and PF-PI controller. The three performance indicators integral time absolute error (ITAE), integral time square error (ITSE) and integral square error (ISE) are used to measure the effectiveness of PF-PI controller optimization. The results show that the optimal torque ripple and speed response curves are obtained by using ITAE as the performance indicator. The conclusions demonstrate that the proposed method provides superior dynamic performance for BLDC motor. Highlights (1) In terms of research content, we propose a new PF-PI controller driven control system based on the traditional BLDC speed control system, and the applicability of three performance indicators on the controller is discussed. (2) In terms of research method, we compare the no-load start, variable speed and sudden addition disturbance load start capabilities of P-PI controller and PF-PI controller, and verify the fast and robustness of PF-PI controller. (3) In the research significance, the PI controller structure is improved and the dynamic performance of BLDC speed control system is enhanced. |
| first_indexed | 2024-04-12T00:36:48Z |
| format | Article |
| id | doaj.art-c696b7b4a28e448197db5c2e5ed40ce5 |
| institution | Directory Open Access Journal |
| issn | 2523-3963 2523-3971 |
| language | English |
| last_indexed | 2024-04-12T00:36:48Z |
| publishDate | 2022-10-01 |
| publisher | Springer |
| record_format | Article |
| series | SN Applied Sciences |
| spelling | doaj.art-c696b7b4a28e448197db5c2e5ed40ce52022-12-22T03:55:08ZengSpringerSN Applied Sciences2523-39632523-39712022-10-0141111410.1007/s42452-022-05179-6Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controllerJun Shi0Qingtao Mi1Weifeng Cao2Lintao Zhou3College of Electrical and Information Engineering, Zhengzhou University of Light IndustryCollege of Electrical and Information Engineering, Zhengzhou University of Light IndustryCollege of Electrical and Information Engineering, Zhengzhou University of Light IndustryCollege of Electrical and Information Engineering, Zhengzhou University of Light IndustryAbstract A brushless DC (BLDC) motor is synchronous motor with trapezoidal/square wave counter-electromotive force, which is a typical example of highly coupled nonlinear systems. In industrial control, BLDC motor drive usually uses proportional–integral (PI) controller to control the speed, but it is very difficult to adjust the scale factors. In this study, we present a particle swarm algorithm-tuned fuzzy logic-PI (PF-PI) controller applied to the speed control system. The objective of this paper is to optimally tune the PI controller parameters to obtain the best drive response. The scale factors are optimized using particle swarm optimized-PI (P-PI) controller and PF-PI controller. The three performance indicators integral time absolute error (ITAE), integral time square error (ITSE) and integral square error (ISE) are used to measure the effectiveness of PF-PI controller optimization. The results show that the optimal torque ripple and speed response curves are obtained by using ITAE as the performance indicator. The conclusions demonstrate that the proposed method provides superior dynamic performance for BLDC motor. Highlights (1) In terms of research content, we propose a new PF-PI controller driven control system based on the traditional BLDC speed control system, and the applicability of three performance indicators on the controller is discussed. (2) In terms of research method, we compare the no-load start, variable speed and sudden addition disturbance load start capabilities of P-PI controller and PF-PI controller, and verify the fast and robustness of PF-PI controller. (3) In the research significance, the PI controller structure is improved and the dynamic performance of BLDC speed control system is enhanced.https://doi.org/10.1007/s42452-022-05179-6Brushless DC motorPerformance indicatorP-PI controllerPF-PI controller |
| spellingShingle | Jun Shi Qingtao Mi Weifeng Cao Lintao Zhou Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller SN Applied Sciences Brushless DC motor Performance indicator P-PI controller PF-PI controller |
| title | Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller |
| title_full | Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller |
| title_fullStr | Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller |
| title_full_unstemmed | Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller |
| title_short | Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller |
| title_sort | optimizing bldc motor drive performance using particle swarm algorithm tuned fuzzy logic controller |
| topic | Brushless DC motor Performance indicator P-PI controller PF-PI controller |
| url | https://doi.org/10.1007/s42452-022-05179-6 |
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