Enhancing Convergence Speed in Control of Synchronous Motors Using Model Predictive Control–MPC with Reference Model

This research paper proposes the application of Model Predictive Control (MPC) with a reference model for achieving faster convergence in the control of synchronous motors. Synchronous motors are are utilized in a variety of industrial contexts. Nevertheless, due to the complex dynamics and inherent uncertainties of these motors, attaining rapid convergence in the control of these motors can be a difficult task. The MPC technique is known for its ability to handle multivariable systems with constraints and uncertainties. By incorporating a reference model into the MPC framework, the control algorithm can anticipate the system’s behavior and make proactive adjustments, leading to faster convergence. This paper explores the implementation and performance evaluation of the MPC approach with a reference model for controlling synchronous motors.