Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm
To address the inherent nonlinearity and strong coupling among rotor displacement, speed, and flux linkage in the composite cage rotor bearingless induction motor (CCR-BIM), an inverse system decoupling control strategy based on a support vector machine (SVM) optimized by the improved simulated anne...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Actuators |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-0825/14/3/125 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850093868075188224 |
|---|---|
| author | Chengling Lu Junhui Cheng Qifeng Ding Gang Zhang Jie Fang Lei Zhang Chengtao Du Yanxue Zhang |
| author_facet | Chengling Lu Junhui Cheng Qifeng Ding Gang Zhang Jie Fang Lei Zhang Chengtao Du Yanxue Zhang |
| author_sort | Chengling Lu |
| collection | DOAJ |
| description | To address the inherent nonlinearity and strong coupling among rotor displacement, speed, and flux linkage in the composite cage rotor bearingless induction motor (CCR-BIM), an inverse system decoupling control strategy based on a support vector machine (SVM) optimized by the improved simulated annealing-genetic algorithm (ISA-GA) is proposed. First, based on the structure and working principle of CCR-BIM, the mathematical model of CCR-BIM is derived, and its reversibility is rigorously analyzed. Subsequently, an SVM regression equation is established, and the SVM kernel function parameters are optimized using the ISA-GA to train a high-precision inverse system decoupling control model. Finally, the inverse system is cascaded with the original system to construct a pseudo-linear system model, achieving linearization and decoupling control of CCR-BIM. To verify the effectiveness and practicability of the proposed decoupling control strategy, the proposed control method is compared with the traditional inverse system decoupling control strategy through simulation and experimentation. Both simulation and experimental results demonstrate that the proposed decoupling control strategy can effectively achieve decoupling control of rotor displacement, rotational speed, and flux linkage in CCR-BIM. |
| format | Article |
| id | doaj-art-cdd64aa2d063446996c3ba0e897ab2d8 |
| institution | DOAJ |
| issn | 2076-0825 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Actuators |
| spelling | doaj-art-cdd64aa2d063446996c3ba0e897ab2d82025-08-20T02:41:48ZengMDPI AGActuators2076-08252025-03-0114312510.3390/act14030125Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic AlgorithmChengling Lu0Junhui Cheng1Qifeng Ding2Gang Zhang3Jie Fang4Lei Zhang5Chengtao Du6Yanxue Zhang7School of Electrical and Photoelectric Engineering, West Anhui University, Lu’an 237012, ChinaSchool of Electrical and Photoelectric Engineering, West Anhui University, Lu’an 237012, ChinaSchool of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Electrical and Photoelectric Engineering, West Anhui University, Lu’an 237012, ChinaSchool of Electrical and Photoelectric Engineering, West Anhui University, Lu’an 237012, ChinaSchool of Electrical and Photoelectric Engineering, West Anhui University, Lu’an 237012, ChinaSchool of Electrical and Photoelectric Engineering, West Anhui University, Lu’an 237012, ChinaSchool of Electronics and Information Engineering, West Anhui University, Lu’an 237012, ChinaTo address the inherent nonlinearity and strong coupling among rotor displacement, speed, and flux linkage in the composite cage rotor bearingless induction motor (CCR-BIM), an inverse system decoupling control strategy based on a support vector machine (SVM) optimized by the improved simulated annealing-genetic algorithm (ISA-GA) is proposed. First, based on the structure and working principle of CCR-BIM, the mathematical model of CCR-BIM is derived, and its reversibility is rigorously analyzed. Subsequently, an SVM regression equation is established, and the SVM kernel function parameters are optimized using the ISA-GA to train a high-precision inverse system decoupling control model. Finally, the inverse system is cascaded with the original system to construct a pseudo-linear system model, achieving linearization and decoupling control of CCR-BIM. To verify the effectiveness and practicability of the proposed decoupling control strategy, the proposed control method is compared with the traditional inverse system decoupling control strategy through simulation and experimentation. Both simulation and experimental results demonstrate that the proposed decoupling control strategy can effectively achieve decoupling control of rotor displacement, rotational speed, and flux linkage in CCR-BIM.https://www.mdpi.com/2076-0825/14/3/125composite cage rotor bearingless induction motorimproved simulated annealing-genetic algorithmsupport vector machinekernel functiondecoupling control |
| spellingShingle | Chengling Lu Junhui Cheng Qifeng Ding Gang Zhang Jie Fang Lei Zhang Chengtao Du Yanxue Zhang Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm Actuators composite cage rotor bearingless induction motor improved simulated annealing-genetic algorithm support vector machine kernel function decoupling control |
| title | Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm |
| title_full | Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm |
| title_fullStr | Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm |
| title_full_unstemmed | Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm |
| title_short | Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm |
| title_sort | inverse system decoupling control of composite cage rotor bearingless induction motor based on support vector machine optimized by improved simulated annealing genetic algorithm |
| topic | composite cage rotor bearingless induction motor improved simulated annealing-genetic algorithm support vector machine kernel function decoupling control |
| url | https://www.mdpi.com/2076-0825/14/3/125 |
| work_keys_str_mv | AT chenglinglu inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm AT junhuicheng inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm AT qifengding inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm AT gangzhang inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm AT jiefang inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm AT leizhang inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm AT chengtaodu inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm AT yanxuezhang inversesystemdecouplingcontrolofcompositecagerotorbearinglessinductionmotorbasedonsupportvectormachineoptimizedbyimprovedsimulatedannealinggeneticalgorithm |