Model Predictive Control Of Dual Induction Motor Single Inverter Drive

Dual induction motor single inverter drives reduce installation space, weight and overall cost. On the other hand, complexity of the control increases significantly, since the condition on each electric machine can vary in a wide range. Today, majority of control algorithms uses cascade structures of linear PI controllers. The consequences of parallel connection of induction motors are addressed by prioritizing of individual motors in the control by a weighting coefficient. The proper choice of the weighting coefficient, which is generally state-dependent time-varying value, strongly affects the overall drive performance. In this paper, state of the art control techniques for dual motor drives are summarized. Based on the detailed analysis of the theoretical background, we formulate a control criteria which solve the whole control problem without additional cascades in a single loop by finite control set model predictive control (FCS-MPC). The extensive simulations are used to analyze and validate the designed control criteria