Hybrid Random SVPWM Strategy for High Order Harmonics Suppression of Permanent Magnet Synchronous Motor Servo Drive System

Author(s):  
Renhui Du ◽  
Qi Liu ◽  
Feifei Bu ◽  
Haihong Qin
Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6627
Author(s):  
Ying Zhou ◽  
Zuyu Wu ◽  
Yutong Wu

This paper presents an intelligent permanent magnet synchronous motor-based servo drive system used in automated piano tuning applications. The permanent magnet synchronous motor-based drives are able to improve the accuracy of the piano tuning process in comparison with the traditional direct-current motor-based and step motor-based servo drives. To explain the techniques, firstly, the structure and principles of the automated piano tuning devices with a surface-mounted permanent magnet synchronous motor-based drive system integrated are introduced, illustrating that it is feasible to implement the proposed piano tuning strategy. Secondly, the piano tuning devices have two functions: low-speed rotation and position holding. To ensure that the surface-mounted permanent magnet synchronous motor can rotate stably over the low-speed range with strong anti-interference capacity, a double closed-loop speed-regulation-based control scheme is employed. And to ensure high position control performance, a fuzzy-adaptive triple closed-loop position-regulation-based control scheme is employed. It terms of the control schemes, it deserves to be mentioned that main contributions include, firstly, the parameters of the proportional integral controllers in the double closed-loop speed-regulation structure is tuned relying on both stability and bandwidth analyses. Then, a fuzzy-adaptive proportional integral controller is specially-designed for the triple closed-loop position-regulation to adapt to the piano tuning applications. Simulation is conducted on a 20 rpm three-phase permanent magnet synchronous motor servo drive-based piano tuning system to validate the proposed piano tuning method and to verify the proposed control techniques.


Author(s):  
Shiqi Zheng ◽  
Xiaoqi Tang ◽  
Bao Song

In this paper, a novel tuning strategy for the fractional order proportional integral and fractional order [proportional integral] controllers is proposed for the permanent magnet synchronous motor servo drive system. The tuning strategy is based on a genetic algorithm–wavelet neural network hybrid method. Firstly, the initial values of the control parameters of the fractional order controllers are selected according to a new global tuning rule, which is based on the genetic algorithm and considers both the time- and frequency-domain specifications. Secondly, the wavelet neural network is utilized to update the control parameters based on the selected initial values in an online manner which improves the capability of handling parameter variations and time-varying operating conditions. Furthermore, to improve the computational efficiency, a recursive least squares algorithm, which provides information to the wavelet neural network, is used to identify the permanent magnet synchronous motor drive system. Finally, experimental results on the permanent magnet synchronous motor drive system show both of the two proposed fractional order controllers work efficiently, with improved performance comparing with their traditional counterpart.


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