Parameter adaptation sensorless control of induction motor based on strong track filter

摘要

The equations of mechanics and torque are introduced into the fourth-order model of induction motor. A seventh-order nonlinear model is obtained via adding load torque and rotor resistance as state variables. The motor states and the rotor resistance are estimated simultaneously using strong track filter (STF). Computer simulations are performed to compare the estimation performance between STF and EKF. The results illustrate that STF can estimate the motor states and the rotor resistance effectively, and its performance is more perfect than EKF's. STF can also satisfy the estimation request running at very low and zero speed, thus it can realize the states estimation with rotor resistance adaptation in the whole operation range.