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2008•Techniques of Automation and ApplicationsRequires access

Speed Sensorless Vector Control Control Based on MRAS

Shen Qun-tai

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Abstract

This paper discusses the sensorless vector control with a method of model reference adaptive system.The normal model can always be affected by the initial value and drift of integral calculation in the conventional speed identifier.This paper presents a new normal model and an adjustable model,and the motor speed is identified by using the neural network.The MATLAB results show that the convergence of the estimation is fast,and the speed is estimated accurately.

About this research paper

What this paper is about

This paper discusses the sensorless vector control with a method of model reference adaptive system.The normal model can always be affected by the initial value and drift of integral calculation in the conventional speed identifier.This paper presents a new normal model and an adjustable model,and the motor speed is identified by using the neural network.The MATLAB results show that the convergence of the estimation is fast,and the speed is estimated accurately.

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Key contribution

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Method / approach

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Available abstract

This paper discusses the sensorless vector control with a method of model reference adaptive system.The normal model can always be affected by the initial value and drift of integral calculation in the conventional speed identifier.This paper presents a new normal model and an adjustable model,and the motor speed is identified by using the neural network.The MATLAB results show that the convergence of the estimation is fast,and the speed is estimated accurately.

Key concepts: MRAS, Control theory (sociology), Identifier, Vector control, Convergence (economics), Computer science, MATLAB, Artificial neural network

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