Speed feedback observation algorithm based on parameter introduction and its application in asynchronous motor

Abstract

In this article, three-phase asynchronous motor and photoelectric encoder are taken as the research objects. In order to solve the problem of delay in the velocity feedback measurement result of asynchronous motor by photoelectric encoder, this article proposes a velocity feedback observation algorithm which introduces parameters according to different velocity instructions. The proposed method ensures that the speed feedback of asynchronous motor can keep good tracking effect under different speed instructions, reduces feedback delay, and the oscillation of speed tracking waveform is small. Stability analysis is also carried out in this article to ensure the reliability of the system. In the whole control system, the position signal output by the photoelectric encoder is the input of the algorithm, and the output of the algorithm is the speed feedback of the system. The proposed method establishes the speed control system model of three-phase asynchronous motor through MATLAB/Simulink for simulation, and the experiment is carried out based on the simulation. The simulation and experiment are compared with the traditional differential velocity measurement method of encoder. The results show that the velocity observation algorithm proposed is verified under different velocity instructions and varying loads, and the system has smaller steady-state error, better dynamic response, and good robustness.

Keywords

Asynchronous motor speed feedback velocity observation parameter introduction

Get full access to this article

View all access options for this article.

References

Zhao

Jiang

, et al. Study on three-phase asynchronous motor based on fuzzy adaptive PI vector control. In: IEEE international conference on information and automation (ICIA), Wuyishan, China, 11–13 August 2018, pp.655–660. New York: IEEE.

Chen

Zhang

Shao

, et al. Simulation study on a novel vector control strategy for asynchronous motor. In: IEEE transportation electrification conference and expo, Busan, South Korea, 1–4 June 2016, pp.72–76. New York: IEEE.

Pan

Zhang

Electromechanical coupling model of AC asynchronous motor drive system based on multiscale method. Jordan J Mech Ind Eng 2021; 15(1): 73–82.

Xing

Design of induction motor speed-sensorless vector control system. In: International symposium on computer, consumer and control (IS3C), Xi’an, China, 4–6 July 2016, pp.563–566. New York: IEEE.

Lee

J-W.

Novel current control assisted V/F control method for high speed induction motor drives. In: 2019 10th international conference on power electronics and ECCE Asia (ICPE 2019 – ECCE Asia), Busan, South Korea, 27–30 May 2019, pp.1293–1296. New York: IEEE.

Chen

Yao

Wang

µ-synthesis-based adaptive robust control of linear motor driven stages with high-frequency dynamics: a case study. IEEE-ASME T Mech 2015; 20(3): 1482–1490.

Zhou

Wang

, et al. A modified modular multilevel converter for motor drives capable of high-torque operation at zero/low motor speeds. IEEE T Circuits II 2021; 68(7): 2493–2497.

Malekpour

Azizipanah-Abarghooee

Teng

, et al. Fast frequency response from smart induction motor variable speed drives. IEEE T Power Syst 2020; 35(2): 997–1008.

Wang

Hou

Speed control of asynchronous motor based on improved deadbeat predictive algorithm. Proc IMechE, Part I: J Systems and Control Engineering 2020; 234(9): 1037–1049.

10.

Choi

Jung

Feedback linearization direct torque control with reduced torque and flux ripples for IPMSM drives. IEEE T Power Electr 2016; 31(5): 3728–3737.

11.

Foo

Zhang

A constant switching frequency based direct torque control of interior permanent magnet synchronous motors with reduced ripples and fast torque dynamics. IEEE T Power Electr 2016; 31(9): 6485–6493.

12.

Wang

, et al. Optimization of torque tracking performance for direct-torque-controlled PMSM drives with composite torque regulator. IEEE T Ind Electron 2020; 67(12): 10095–10108.

13.

Liu

Zhang

Zhao

, et al. Research on speed tracking of asynchronous motor based on fuzzy control and vector control. In: 2020 39th Chinese control conference (CCC), Shenyang, China, 27–29 July 2020, pp.2144–2149. New York: IEEE.

14.

Tian

. Model reference adaptive vector control of asynchronous motor without speed sensor. In: 2016 35th Chinese control conference (CCC), Chengdu, China, 27–29 July 2016, pp.3195–3199. New York: IEEE.

15.

Zhang

. Induction motor control system based on FOC algorithm. In: IEEE 8th joint international information technology and artificial intelligence conference (ITAIC), Chongqing, China, 24–26 May 2019, pp.1544–1548. New York: IEEE.

16.

Nisha

Lakaparampil

Ushakumari

Effect of power factor on torque capability of FOC induction machine in field weakening region for propulsion systems. Electr Eng 2017; 99(3): 1065–1072.

17.

Morozov

Dobroskok

Lavrinovskiy

, et al. Stability analysis of mechanical coupled two-motor asynchronous electric drive. In: Proceedings of the 2017 IEEE Russia section young researchers in electrical and electronic engineering conference, St. Petersburg, 1–3 February 2017, pp.953–957. New York: IEEE.

18.

Zhong

Active disturbance rejection control and energy consumption of three-phase asynchronous motor based on dynamic system’s decoupling. Sustain Energ Technol Assess 2021; 47: 101338.

19.

Talla

Leu

Šmídl

, et al. Adaptive speed control of induction motor drive with inaccurate model. IEEE T Ind Electron 2018; 65(11): 8532–8542.

20.

Xie

Qiu

Zhe

Optimal speed-torque control of asynchronous motor for electric cars in the field-weakening region based on voltage vector optimization. IEEE T Power Electr 2022; 37(1): 830–842.

21.

Wang

Hao

Song

, et al. Study on the temperature drift adaptive compensation algorithm of a magneto-electric encoder based on a simple neuron. J Power Electron 2014; 14(6): 1254–1262.

22.

Hao

Liu

Hao

Study on a novel absolute magnetic encoder. In: IEEE international conference on robotics and biomimetics, Bangkok, Thailand, 22–25 February 2009, pp.1773–1776. New York: IEEE.

23.

Feng

Hao

, et al. Development of a combined magnetic encoder. Sensor Rev 2016; 36(4): 386–396.

24.

Wang

, et al. Enhanced predictive model based deadbeat control for PMSM drives using exponential extended state observer. IEEE T Ind Electron 2021; 69(3): 2357–2369.

25.

Xie

, et al. Research on low speed control of permanent magnet synchronous motor based on state observer. In: IEEE 2011 4th international conference on biomedical engineering and informatics (BMEI), Shanghai, China, 15–17 October 2011, pp.2018–2022. New York: IEEE.

26.

Shi

Xie

, et al. Speed sensorless vector control of induction motor based on adaptive full-order flux observer. In: Proceedings of the 2016 IEEE 11th conference on industrial electronics and applications (ICIEA), Hefei, China, 5–7 June 2016, pp.124–127. New York: IEEE.

27.

Bialon

Niestorj

Michalak

, et al. Induction motor PI observer with reduced-order integrating unit. Energies 2021; 14(16): 4906.

28.

Chiasson

Bodson

, et al. A differential-algebraic approach to speed estimation in an induction motor. IEEE T Automat Contr 2006; 51(7): 1172–1177.