Design of Sensorless Speed Control System for Permanent Magnet Linear Synchronous Motor Based on Fuzzy Super-Twisted Sliding Mode Observer

Li, Zheng; Wang, Shaohua; Feng, Shengdi; Zhu, Yaguang; Sun, Hexu

doi:10.3390/electronics11091394

Cited by 11 publications

(9 citation statements)

References 18 publications

(21 reference statements)

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“…Li, Z. et al in [12] present a sensorless control algorithm for permanent magnet linear synchronous motors (PMLSMs) that enhances tracking capability and estimation accuracy. The system combines a continuous terminal sliding mode controller (CTSMC) with a fuzzy super twisting sliding mode observer (FSTSMO).…”

Section: Review Of Published Papersmentioning

confidence: 99%

Sliding Mode Control in Dynamic Systems

2023

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Section: Review Of Published Papersmentioning

confidence: 99%

Sliding Mode Control in Dynamic Systems

2023

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“…The main sensorless control techniques currently used for permanent magnet synchronous motors are the extended Kalman filter method, the model reference adaptive method, and the sliding mode observer method. In noisy environments, the extended Kalman filter method can have good results, but the complex matrix operation in it increases the computational burden of the control system and limits the application of this method in the high-speed range [4][5] .The main idea of MARS is to construct the motor equations without the position parameters as the reference model and the equations of the parameters to be estimated as the adjustable model. An adaptive law is constructed using the difference between the two model outputs so that the output of the adjustable model tracks the reference model output.…”

Section: Introductionmentioning

confidence: 99%

PMSM sensorless control based on sliding mode control with fuzzy variable gain STA-SMO

Zhou,

Nie,

Zhou

et al. 2023

Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023)

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A fuzzy variable-gain super-spiral sliding mode observer is proposed to address the problems of jitter and low estimation accuracy caused by the use of constant sliding mode gain in the traditional Sliding Mode Observer (SMO). The fuzzy controller is introduced to replace the traditional observer with a fixed sliding mode gain by a variable sliding mode gain, and to improve the estimation accuracy and system robustness by online adjustment of the sliding mode gain. Secondly, to address the problems of large overshoot and slow response speed caused by the tacho loop PI controller in the traditional control system, a new convergence rate based tacho sliding mode controller is proposed to reduce the system overshoot and improve the response speed. The stability of the proposed sliding mode controller is proved by using Liapunov's stability theorem. Finally, Matlab/Simulink simulation is used to verify that the proposed improved control system has faster response speed, higher estimation accuracy and better system jitter suppression.

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“…To address the effects caused by SMC, researchers have combined it with other control methods to optimize control performance. It includes adaptive sliding mode control [ 15 , 16 ], neural network sliding mode control [ 17 , 18 , 19 ] and fuzzy sliding mode control [ 20 , 21 ]. Among them, the development of adaptive control is relatively mature and can adapt to the state changes in the system by adjusting the characteristics of the control system.…”

Section: Introductionmentioning

confidence: 99%

Integrated Controller Design and Application for CNC Machine Tool Servo Systems Based on Model Reference Adaptive Control and Adaptive Sliding Mode Control

Zhang,

Li,

Gai

et al. 2023

Sensors

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In order to reduce the effect of nonlinear friction and time-varying factors on the servo system of a computer numerical control (CNC) machine tool and improve its motion control accuracy, this paper uses an adaptive sliding mode control (ASMC) method based on model reference adaptive control (MRAC). The method adopts ASMC in the control outer loop and obtains the optimal control parameters by making the sliding mode control (SMC) law continuous and adaptively estimating the control parameters. At the same time, MRAC is used in the control inner loop to enhance the “invariance” of the controlled object so that the switching gain of SMC can satisfy the disturbance matching condition even under lesser conditions. Simulation and experimental results show that compared with the traditional SMC, the ASMC based on MRAC proposed in this paper effectively reduces the influence of nonlinear friction on the system performance, and the reduction in following error reaches 71.2%, which significantly improves the motion control accuracy of the control system. The spectral analysis of the following errors shows that the maximum magnitude reduction rate of the high-frequency chattering is 89.02%, which significantly reduces the effect of the high-frequency chattering and effectively improves the stability performance of the control system.

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Design of Sensorless Speed Control System for Permanent Magnet Linear Synchronous Motor Based on Fuzzy Super-Twisted Sliding Mode Observer

Cited by 11 publications

References 18 publications

Sliding Mode Control in Dynamic Systems

Sliding Mode Control in Dynamic Systems

PMSM sensorless control based on sliding mode control with fuzzy variable gain STA-SMO

Integrated Controller Design and Application for CNC Machine Tool Servo Systems Based on Model Reference Adaptive Control and Adaptive Sliding Mode Control

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