A New Performance Optimization Method for Linear Motor Feeding System
The linear motor feeding system is a typical electromechanical coupling system. Conventional characteristic analyses of electromechanical coupling often overlook the influence of flexible deformation in critical components of the linear motor feeding system. Moreover, when employing genetic algorith...
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| Format: | Article |
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MDPI AG
2023-06-01
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| Series: | Actuators |
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| Online Access: | https://www.mdpi.com/2076-0825/12/6/233 |
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| author | Zeqing Yang Wei Cui Wenbo Zhang Zhaohua Wang Bingyin Zhang Yingshu Chen Ning Hu Xiaoyang Bi Wei Hu |
| author_facet | Zeqing Yang Wei Cui Wenbo Zhang Zhaohua Wang Bingyin Zhang Yingshu Chen Ning Hu Xiaoyang Bi Wei Hu |
| author_sort | Zeqing Yang |
| collection | DOAJ |
| description | The linear motor feeding system is a typical electromechanical coupling system. Conventional characteristic analyses of electromechanical coupling often overlook the influence of flexible deformation in critical components of the linear motor feeding system. Moreover, when employing genetic algorithms to optimize servo system PID control parameters, slow convergence, nonconvergence, or premature convergence problems may arise. To address these issues, this paper proposes a new performance optimization method for a linear motor feeding system. The method uses a combination of “multi-body theory + finite element” to accurately account for the flexible deformation of critical components of the feeding system, establishes a rigid–flexible electromechanical coupling model of the linear motor feeding system, and optimizes the PID parameters of the established model with an improved adaptive genetic algorithm. Simulation results demonstrate that, when utilizing an adaptive genetic algorithm to optimize the rigid–flexible electromechanical coupling model and a control system model that disregards flexible body deformation, the system achieves stability in 0.02 s and 0.027 s with overshoots of 13% and 27%, respectively. These outcomes confirm the accuracy and importance of considering flexible body deformation in the optimization performance of a linear motor feeding system. At the same time, the time required to reach the steady state of the rigid–flexible electromechanical coupling model optimized by the adaptive genetic algorithm is shortened from 0.035 s to 0.02 s. The sinusoidal signal response curve of the optimized system does not exhibit any peak overshoot compared with that of the nonoptimized system, and the response speed is also faster. These results demonstrate the effectiveness of the rigid–flexible electromechanical coupling model optimized by the nonlinear adaptive genetic algorithm. The displacement response curves of the linear motor feeding system under different workbench loads are obtained through experiments and compared with those obtained from simulations to verify the established model and the correctness of the proposed method. |
| first_indexed | 2024-03-11T02:53:39Z |
| format | Article |
| id | doaj.art-44124abfc1434883963fe685a57ef29c |
| institution | Directory Open Access Journal |
| issn | 2076-0825 |
| language | English |
| last_indexed | 2024-03-11T02:53:39Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Actuators |
| spelling | doaj.art-44124abfc1434883963fe685a57ef29c2023-11-18T08:48:39ZengMDPI AGActuators2076-08252023-06-0112623310.3390/act12060233A New Performance Optimization Method for Linear Motor Feeding SystemZeqing Yang0Wei Cui1Wenbo Zhang2Zhaohua Wang3Bingyin Zhang4Yingshu Chen5Ning Hu6Xiaoyang Bi7Wei Hu8School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaSchool of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, ChinaWorld Transmission Technology (Tianjin), Intersection of Gaoxin Avenue and Jingming Road, Beichen Science Park, Tianjin 300130, ChinaThe linear motor feeding system is a typical electromechanical coupling system. Conventional characteristic analyses of electromechanical coupling often overlook the influence of flexible deformation in critical components of the linear motor feeding system. Moreover, when employing genetic algorithms to optimize servo system PID control parameters, slow convergence, nonconvergence, or premature convergence problems may arise. To address these issues, this paper proposes a new performance optimization method for a linear motor feeding system. The method uses a combination of “multi-body theory + finite element” to accurately account for the flexible deformation of critical components of the feeding system, establishes a rigid–flexible electromechanical coupling model of the linear motor feeding system, and optimizes the PID parameters of the established model with an improved adaptive genetic algorithm. Simulation results demonstrate that, when utilizing an adaptive genetic algorithm to optimize the rigid–flexible electromechanical coupling model and a control system model that disregards flexible body deformation, the system achieves stability in 0.02 s and 0.027 s with overshoots of 13% and 27%, respectively. These outcomes confirm the accuracy and importance of considering flexible body deformation in the optimization performance of a linear motor feeding system. At the same time, the time required to reach the steady state of the rigid–flexible electromechanical coupling model optimized by the adaptive genetic algorithm is shortened from 0.035 s to 0.02 s. The sinusoidal signal response curve of the optimized system does not exhibit any peak overshoot compared with that of the nonoptimized system, and the response speed is also faster. These results demonstrate the effectiveness of the rigid–flexible electromechanical coupling model optimized by the nonlinear adaptive genetic algorithm. The displacement response curves of the linear motor feeding system under different workbench loads are obtained through experiments and compared with those obtained from simulations to verify the established model and the correctness of the proposed method.https://www.mdpi.com/2076-0825/12/6/233linear motor feeding systemrigid–flexible electromechanical couplingperformance optimizationadaptive genetic algorithm |
| spellingShingle | Zeqing Yang Wei Cui Wenbo Zhang Zhaohua Wang Bingyin Zhang Yingshu Chen Ning Hu Xiaoyang Bi Wei Hu A New Performance Optimization Method for Linear Motor Feeding System Actuators linear motor feeding system rigid–flexible electromechanical coupling performance optimization adaptive genetic algorithm |
| title | A New Performance Optimization Method for Linear Motor Feeding System |
| title_full | A New Performance Optimization Method for Linear Motor Feeding System |
| title_fullStr | A New Performance Optimization Method for Linear Motor Feeding System |
| title_full_unstemmed | A New Performance Optimization Method for Linear Motor Feeding System |
| title_short | A New Performance Optimization Method for Linear Motor Feeding System |
| title_sort | new performance optimization method for linear motor feeding system |
| topic | linear motor feeding system rigid–flexible electromechanical coupling performance optimization adaptive genetic algorithm |
| url | https://www.mdpi.com/2076-0825/12/6/233 |
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