LAUSR

This work deals with the optimization of sensorless field-oriented control of an induction motor taking into account of magnetic saturation effects. We propose a double optimization (in the point of view of dynamic and energetic performances) of sensorless field-oriented control of induction motor. This control is associated to a Luenberger type interconnected observers. Particle swarm optimization algorithm is used notably to determine the optimal gains of the observers as well as the optimal parameters of the regulators. This algorithm guarantees the stability and the global convergence of the system. The sensorless control takes into account all operating range of the machine (very low speed, low speed, high speed with or without load torque). Regarding the energetic optimization, the reference of the rotor flux is generated using another developed algorithm that permits us to dynamically determine the optimal rotor flux for each given value of motor load and speed. Numerical simulations are carried out each time to confirm theoretical predictions.