Implementation of a Mixed Recursive Least-squares and Kalman Filter Approach in Parameters, Flux, and Speed Estimation for Vector-controlled Induction Motor Drives
| Autor: | G. Maragliano, M. Marchesoni |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Recursive least squares filter
Engineering Vector control Minimum mean square error Estimation theory business.industry Mechanical Engineering Energy Engineering and Power Technology Estimator Control engineering Ranging Kalman filter Control theory Electrical and Electronic Engineering business Induction motor |
| Zdroj: | Electric Power Components and Systems. 36:359-386 |
| ISSN: | 1532-5016 1532-5008 |
| DOI: | 10.1080/15325000701658516 |
| Popis: | Today, vector-controlled induction motor drives play a major role in several applications ranging from transport to industrial applications and so on. However, vector control is quite complex and two aspects are always of great concern: electrical parameters real-time knowledge and speed-sensorless control. In this article, the development of a recurrent least-squares estimator devoted to the real-time knowledge of the electrical parameters of the motor is presented first. Subsequently, the implementation of a Kalman flux and speed estimator that only uses the electrical variables of the motor is also presented, and its exploitation to improve the least-squares parameters estimation process and the related results are shown and discussed. |
| Databáze: | OpenAIRE |
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