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State and Parameter Estimation for Field-oriented Control of Induction Machine Based on Unscented Kalman Filter

Modern electric machines are required to have the best possible dynamic performances. In induction machines this is achieved by control strategies that are applied with respect to the flux in the air gap and therefore they require precise information on flux position. This paper proposes an observer with autotuning capability that uses the unscented Kalman filter algorithm for providing on-line estimation of states and parameters of the fundamental wave model of the machine. The algorithm uses power converter reference values of stator voltages, measured stator currents and rotor speed as inputs. Such observer provides accurate estimates of flux position and fundamental stator currents required for e.g. field-oriented control, taking into account machine parameters variability. Design procedure of the observer is presented and both simulation and experimental results are provided.

Induction Machine; Parameter and State Estimation; Dual Unscented Kalman Filter; Flux Position Estimation

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