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Model Predictive speed control of PMSM in MATLAB

Model Predictive speed control of PMSM in MATLAB


We'll delve into the realm of predictive speed control for Permanent Magnet Synchronous Motors (PMSM) using a Model Predictive Controller (MPC). This advanced control strategy aims to achieve precise speed regulation by predicting and optimizing the control actions. We'll explore the assembly model of state control for PMSM, initially utilizing a Voltage-Angle (VA) controller for speed regulation. Later, we'll transition to Model Predictive Control and observe its benefits in terms of response time, overshoot, and overall performance.

Assembly Model Overview:

  1. Objective - Speed Control: The primary objective is to regulate the speed of a PMSM. The actual speed is measured and compared with the reference speed to ensure accurate control.

  2. VA Controller: A VA controller processes the speed error and generates the IQ reference, ensuring effective speed regulation. The rotor angle is also considered in this process.

  3. Conversion to ABC Form: The IQ reference generated is converted from DQ to ABC form, simplifying further processing.

  4. Control Signal Generation: The ABC-form current of the PMSM is measured and processed through a comparator to generate the control signal for the inverter.

  5. Load Torque Simulation: The simulation includes the introduction of load torque, allowing the measurement of PMSM parameters such as voltage, current, speed, and torque.

Implementation of Model Predictive Control:

  1. Transfer Function Model: A transfer function model of the PMSM system is generated using the System Identification Toolbox in MATLAB.

  2. Model Predictive Controller (MPC): The designed MPC receives actual speed, reference speed, and disturbance inputs. It generates the IQ reference, controlling the inverter to regulate the PMSM speed.

  3. Comparison - VA Controller vs. MPC: The tutorial illustrates the response of the system with both controllers. The MPC response showcases quick and precise speed control without overshoot.


In conclusion, the tutorial demonstrates the transition from a conventional VA controller to an advanced Model Predictive Controller for PMSM speed control. The MPC's benefits include quick response, absence of overshoot, and efficient speed regulation. The MATLAB simulation provides insights into the effectiveness of model predictive control in enhancing the performance of PMSM speed control systems.

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