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Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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PMSM sensorless control based on super-twisting algorithm sliding mode observer with the IAORLS parameter

Hui Zhang1, Peng Ran2, Zehua Zhang2

  • 1College of Computer and Control Engineering, Qiqihar University, Qiqihar, 161000, China. zh@qqhru.edu.cn.

Scientific Reports
|July 2, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new algorithm to accurately identify surface-mounted permanent magnet synchronous motor (SPMSM) parameters. This improves sensorless control by reducing oscillations and enhancing rotor position and speed estimation.

Keywords:
Information acquisition optimizerParameter identificationRecursive least squareSensorless controlSuper-twisting sliding mode observerSurface-mount permanent magnet synchronous motor

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Area of Science:

  • Electrical Engineering
  • Control Systems
  • Motor Drives

Background:

  • Sliding Mode Observers (SMO) in sensorless control of SPMSMs suffer from high-frequency oscillations.
  • Parameter variations due to magnetic saturation and temperature affect motor performance.

Purpose of the Study:

  • To propose a novel algorithm for accurate real-time parameter identification in SPMSMs.
  • To mitigate high-frequency oscillations and improve the accuracy of sensorless control.

Main Methods:

  • Developed an Information Acquisition Optimized Recursive Least Squares (IAORLS) algorithm with an optimized forgetting factor.
  • Utilized forward Euler method for discretizing SPMSM stator voltage equations for parameter identification.
  • Integrated identified parameters into a Super Twisting Algorithm Sliding Mode Observer (STA-SMO).

Main Results:

  • The IAORLS algorithm efficiently identifies motor parameters.
  • Real-time parameter updates in STA-SMO prevent performance degradation due to parameter mismatches.
  • Reduced high-frequency oscillations in back-EMF observation, enhancing rotor position and speed estimation accuracy.

Conclusions:

  • The proposed IAORLS-STA-SMO approach effectively addresses oscillations and parameter variations in SPMSM sensorless control.
  • The method demonstrates improved accuracy and reliability in rotor position and speed estimation.
  • Validated through simulations and experimental results.