Novel strategies in the Model-based Optimization and Control of Permanent Magnet DC motors. (May 2015) - Dhinakaran, P.; Manamalli, D.
Abstract: Model-based optimization and control of complex systems is gaining popularity due to its straightforward applicability to multivariate systems. The objective of this paper is to highlight the performance of Simplified Predictive Control (SPC) and Shifted Dynamic Matrix Control (SDMC) on a Permanent Magnet Direct Current motor (PMDC) drive. The overall control of the PMDC motor drive by the control schemes mentioned above explicitly utilizes a dynamic mathematical model of the nonlinear system, which relates the voltage being fed to the drive and the angular velocity being monitored. The process model implemented in the formulation is the step response model and simulation results have been obtained by varying the tuning factors, such as the prediction horizon, control horizon and shifting factor, to study the impact of model-based control on the PMDC motor drive. Analysis of the system matrix unconditionality has also been performed for the simplified predictive control and shifted dynamic matrix control schemes, and the simulation results show satisfactory performance along the reference trajectory.