A SOSM Control for Induction Motor Using ANN-based Sensorless Speed and Flux Estimation under Parametric Uncertainty in FOC Control Method

In this paper, a second order-sliding mode (SOSM) control strategy for Field Oriented Control (FOC) of induction motor (IM) is proposed that satisfying requirements of reliable dynamics and steady state performance. The proposed control structure is a state of the development of FOC utilized SOSM in the inner loop that employ the artificial neural network (ANN) to estimate the rotor flux and motor speed. The SOSM controller designed based on model of induction motor (IM) that include torque control loop (inners loop) and speed tracking control (outer loop). Based on the sliding state convergence property, the state variables track the reference values. By analyzing the theory, the desired performance of the proposed control system proven for various situations. The proposed control considerably ameliorates specified disadvantages of the FOC and DTC, such as the sensitivity to motor parameter variations. The simulation results indicate the correctness of the control algorithm under the uncertainty in parameters and load variations. Keywords, (FOC, ANN’s, Uncertainty, estimation, SOSM, Robust)