6533b85bfe1ef96bd12bb6b7
RESEARCH PRODUCT
Extended Kalman Filter for sensorless control of induction motors
Filippo D'ippolitoFrancesco Alongesubject
State variableEngineeringbusiness.industryControl engineeringKalman filterInvariant extended Kalman filterExtended Kalman filterSettore ING-INF/04 - AutomaticaComputer Science::Systems and ControlControl theoryFilter (video)Control systemFull state estimation sensorless control experimental validation.TorquebusinessInduction motordescription
This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the designed EKF which gives the feedback variables. Comparison with a fifth order EKF, which does not include mechanical equation in the model, is carried out by means of simulation in Matlab/Simulink environment.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2010-07-01 | 2010 First Symposium on Sensorless Control for Electrical Drives |