LMI-based Sensor-less Robust Predictive Control of Induction Motors by Torque Disturbance

In this paper, a new robust predictive control method for induction motors (IMs) is discussed. Linear matrix inequalities (LMIs) are employed, and feedback and observer matrices are designed in the presence of disturbances. To improve accuracy, a nonlinear motor model with parameter uncertainties and perturbations is used. With this nonlinear model, rotor speed is treated as one of the state variables and can be directly controlled using the proposed method. Additionally, uncertainty is incorporated to compensate for modeling errors or parameter mismatches. Finally, the effect of load torque is considered as a disturbance input to the system. Simulations and experimental results are presented at the end.