Speed Estimation of Three-Phase Induction Motor Using Kalman Filter

2018 ◽  
Vol 13 (4) ◽  
pp. 267
Author(s):  
Sasiya Udomsuk ◽  
Kongpol Areerak ◽  
Tidarut Areerak ◽  
Kongpan Areerak
Keyword(s):  
Kalman Filter ◽  
Induction Motor ◽  
Speed Estimation ◽  
Three Phase

Speed Estimation of a Three Phase Induction Motor Using Stator Dynamic Strain Measurement by Fiber Bragg Grating Sensor based in SVR

2021 ◽  
Author(s):  
Rafael Mancuso Paraiso Cavalcanti ◽  
Jaqueline Bierende ◽  
Beatriz Brusamarello ◽  
Jean Carlos Cardozo Da Silva ◽  
Giovanni Alfredo Guarneri ◽  
...  
Keyword(s):  
Fiber Bragg Grating ◽  
Induction Motor ◽  
Strain Measurement ◽  
Fiber Bragg Grating Sensor ◽  
Dynamic Strain ◽  
Bragg Grating ◽  
Speed Estimation ◽  
Three Phase ◽  
Bragg Grating Sensor

scholarly journals Kalman Filtering Applied to Induction Motor State Estimation

2020 ◽  
Author(s):  
Yassine Zahraoui ◽  
Mohamed Akherraz
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Induction Motor ◽  
Kalman Filtering ◽  
Speed Estimation ◽  
Stochastic Algorithm ◽  
State Variables ◽  
Extended Kalman Filtering ◽  
Filtering Theory ◽  
State Observation

This chapter presents a full definition and explanation of Kalman filtering theory, precisely the filter stochastic algorithm. After the definition, a concrete example of application is explained. The simulated example concerns an extended Kalman filter applied to machine state and speed estimation. A full observation of an induction motor state variables and mechanical speed will be presented and discussed in details. A comparison between extended Kalman filtering and adaptive Luenberger state observation will be highlighted and discussed in detail with many figures. In conclusion, the chapter is ended by listing the Kalman filtering main advantages and recent advances in the scientific literature.

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