Torque Control of Induction Machines Using QRM-MPC Approach

Abstract:
Model Predictive Control is a promising technique for electric drives, as it enables optimization for multiple parameters and offers reliable operation with non-linear systems. In this paper, a novel approach is used that aims to harness the advantages of both finite and continuous set model predictive methods in converter-fed AC drive control. The applied method calculates seven predicted states and assigns cost function values to these as a finite set approach would. Then a Quadratic Regression Model is fit upon this cost function data to extend it to the entire modulation region continuously. This transforms the problem into a continuous control set approach. The associated quadratic programming problem can be solved simply and efficiently due to this formulation without the need of iteration. The optimal voltage vector can be applied via Pulse Width Modulation. Simulation and experimental results verify the operation of the predictive torque control for Induction Machines with the proposed method.