An Extended Kalman Filter Approach for Flux-Sensorless Control of a Linearized and Decoupled Induction Motor Drive
This study uses a robust input-output linearization via feedback control in order to assure a good dynamic performance, stability and a decoupling of the stator currents for an induction motor in a field-oriented (d, q) coordinate. However, this control requires the knowledge of certain variables (rotor flux, torque) that are difficult to access or simply impossible to measure and also the rotor time constant variation can induce a performance degradation of the system. Thus, a fifth-order Discrete-time extended Kalman filter approach is proposed for on-line estimation of rotor flux, currents, rotor time constant and torque in an induction motor. The interesting simulations and experimental results obtained on a testing bench for a 5.5 kW induction motor permit to validate the effectiveness and good performance of the proposed nonlinear control and extended Kalman filter algorithm in the presence of parameter variation, modeling uncertainty and measurement noise.
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