OpenFields

Sensorless control of DC and induction motors using Kalman Filtering

The paper studies sensorless control and rotor speed or acceleration estimation, for DC (direct current) and induction motors, using Kalman Filtering techniques

Year of Publication2009

The paper studies sensorless control and rotor speed or acceleration estimation, for DC (direct current) and induction motors, using Kalman Filtering techniques. First the case of a DC motor is considered and Kalman Filter-based control is implemented. Next the nonlinear model of a field-oriented induction motor is examined and the motor's angular velocity is estimated by an Extended Kalman Filter which processes measurements of the rotor's angle. Sensorless control of the induction motor is again implemented through feedback of the estimated state vector. Finally, a state estimation-based control loop is implemented using the Unscented Kalman Filter. The efficiency of the Kalman Filter-based control schemes, for both the DC and the induction motor models, is evaluated through simulation experiments.

This item is categorised as follows

Additional keywords/tags

kalman filtersensorless controlunscented kalman filterdc motorsextended kalman filterinduction motors
Organisation Logo for Harper Adams University

Supporting the development of the national rural economy.

Website

What Next...?

This is a brief summary of an item in the OpenFields Library. This free online library contains items of interest to practitioners and researchers in the agricultural and landbased industries.