S&M Young Researcher Paper Award 2020
Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

S&M Young Researcher Paper Award 2021
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Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Adaptive Speed Estimation with Genetic Algorithm for Vector- controlled Permanent Magnet Synchronous Motor Drive

Yung-Chang Luo, Song-Yi Xie, Chia-Hung Lin, and Ying-Piao Kuo

(Received June 21, 2021; Accepted September 8, 2021)

Keywords: vector-controlled (VC), permanent magnet synchronous motor (PMSM) drive, speed estimation, model reference adaptive system (MRAS), genetic algorithm (GA)

An adaptive speed estimation scheme was established for a vector-controlled (VC) permanent magnet synchronous motor (PMSM) drive. The current and voltage of the stator were used to develop a decoupling VC PMSM drive, and the speed, d-axis, and q-axis stator current control loops were designed using the linear PMSM mathematical model. Hall effect current sensors were used to measure the current of the PMSM. A model reference adaptive system (MRAS) was used to develop a speed estimation scheme based on the reactive power of the PMSM. The pole placement was used to design the d-axis and q-axis stator current controllers, and the speed controller was designed using the genetic algorithm (GA). The MATLAB/Simulink® toolbox was used to establish the simulation scheme, and all the control algorithms were realized by a microprocesser control card. Simulation and experimental results (including the estimated rotor speed, stator current, estimated electromagnetic torque, stator flux position angle, and stator flux locus) confirmed the effectiveness of the proposed approach.

Corresponding author: Yung-Chang Luo

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