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.

title = "Extended Kalman Filter for Sensorless Control of Induction Motors",

abstract = "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.",

author = "Francesco Alonge and Filippo D'Ippolito",

year = "2010",

language = "English",

pages = "107--113",

}

TY - CONF

T1 - Extended Kalman Filter for Sensorless Control of Induction Motors

AU - Alonge, Francesco

AU - D'Ippolito, Filippo

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.