PMSM Real-Time Vector Control (FOC) Simulation with Simulink

If the transfer function model of the plant is a first order model, then a PI controller is used.

The discussion on the desired closed-loop characteristic polynomial with respect to the choice of natural frequency ?n (or bandwidth) and damping coefficient ? will be discussed.

PID control is generally required when controlling the angular position of an AC drive. All industrial AC drives for speed and position control use a PI cascade control structure.

Depending on the application, a wide variety of power electronics devices have been developed, which differ in the type of solid-state switches, construction topology and designs. The common function of these devices is to control the power flow by varying the on/off time of each switch. Among them, the 2-Level Voltage Source Inverter (2L-VSI) is the most common mechanism for controlling three-phase AC machines.

To reduce the effects of the harmonics, carrier based PWM techniques with sequence injection are used. To enhance the output voltage from the PWM inverter using carrier-based scheme, third harmonic injection in the modulating signal is done.

The SVPWM technique is one of the most popular PWM techniques due to a higher DC bus voltage use and easy digital realization.

The concept of the SVPWM relies on the representation of the inverter output as space vectors or space phasors. Space vector representation of the output voltages of the inverter is realized and simulated for the implementation of SVPWM.

However, in a PMSM motor, the torque and flux are not naturally decoupled. The stator windings in a PMSM motor produce both the torque and flux, and the two components are coupled together. To decouple them, a mathematical transformation such as the Park and Clarke transformation is used. This transformation allows the torque and flux components to be separated into two orthogonal axes, with the torque component aligned with the rotor's magnetic field and the flux component aligned with the stator's magnetic field. Once the torque and flux are decoupled, it becomes easier to control them independently and achieve high performance and efficiency in the motor.

The analysis of a three-phase system could be considerably simplified by the use of vector-based approaches.

We introduce here the concept of space vector before proposing a model of a PMSM.

This video presents the two most widely adopted reference frames and their relationships, which are the stationary reference frame and the synchronous reference frame.

Another reference system is the d-q reference system, in which the direct axis (d) is always aligned with the three-phase current generated by the permanent magnets in the rotor, and the q axis is in quadrature. Since in steady state the rotor rotates at the same speed as the grid frequency, it is also called the synchronous frame for PMSM.

The behavior of three-phase machines is normally described by their voltage and current equations. The coefficients of the differential equations that describe their behavior are time-varying (except when the rotor is at rest). The mathematical modeling of such a system is usually very complex, because the combinations of fluxes, induced voltages and currents vary continuously as the electrical circuit is in relative motion. To analyze such a complex electrical machine, mathematical transformations are often used to decouple variables and solve equations with time-varying quantities, relating all variables to a common frame of reference.

Among the various transformation methods available, the most well-known are the following:

- Clarke transformation

- Park transformation

The control of a Permanent Magnet Synchronous Motor (PMSM), when represented by an electrical model in a d-q reference frame, can be compared to the control of DC motors. In other words, the principles of controlling a PMSM using its electrical model in the d-q reference frame are similar to the principles used in controlling DC motors.

In this Simulink simulation, we will compare the physical model of a Permanent Magnet Synchronous Motor against models from the Simscape/Electrical/Specialized Power Systems library. The PMSM's physical parameters are defined and using these parameters, by using Simulink we will solve the differential equations from a previous video to obtain the responses of id, iq currents and velocity omega_e.

In this video, we will explore the Analogies Between DC Motor Control and PMSM FOC. By examining key concepts and control strategies, we will gain a deeper understanding of the similarities and shared approaches between these two types of motor control. In a DC motor, the commutator changes the direction of current flow in the armature windings at the appropriate time to maintain this 90-degree relationship between the current and the rotor flux. Similarly, in PMSM FOC, the MPTA control algorithm adjusts the phase angle of the stator current to keep it at a 90-degree angle to the rotor flux, which maximizes the torque output of the motor. By maintaining this 90-degree relationship between the current and the rotor flux, both systems are able to operate efficiently and effectively.

Remember that vector control was born out of the desire to control AC motors in the same way that we can control brushed DC motors. To control the torque, we need to control the motor current. The current control can be divided into 4 steps:

1, Measure the current already flowing in the motor.

2, Compare the measured current, with the desired current, and generate an error signal.

3, Amplify the error signal to generate a correction voltage.

4, Modulate the correction voltage across the motor terminals.

In the implementation of the control law, the control signals vd and vq are converted into the signals valpha and vbeta using the inverse Park transform, and then into the three-phase voltage signals va, vb, and vc, which are implemented using a voltage source inverter that usually consists of a DC power supply and several semiconductor switches.

PMSM torque control is commonly used in a variety of applications, prominently seen in the electric car industry. In this context, we will delve into the process of designing PI control systems to accomplish the task of torque control.

In the design of the control system, a cascading configuration of feedback and feedforward control is set up for the purpose of speed regulation. Within the drive control mechanisms, two PI controllers are utilized to manage the currents of the d-axis and q-axis. Meanwhile, an additional PI controller is positioned in the outer-loop, tasked with fulfilling the main control goal of speed regulation.

Understand the importance of cascaded PI structures, voltage/current constraints, and anti-windup design for PMSM drives. This video sets the stage for practical implementation.

Learn how to build a reusable embedded MATLAB PI  controller function and integrate it into a full PMSM simulation for current and speed control. Follow the step-by-step tutorial in the resources.

This course introduces you to the DSP-based implementation of speed control for Permanent Magnet Synchronous Motors (PMSMs) using Field-Oriented Control (FOC).

You will learn how modern digital signal processors (DSPs) provide the real-time computing power and peripherals needed for high-performance motor control.

In this lecture, you will explore the hardware design aspects of sensorless PMSM FOC.
We cover current sensing topologies (low-side, two-shunt, single-shunt) and the role of precision amplifiers like the INA303. You’ll also study inverter design using IGBT modules, signal conditioning for protection, and how these elements impact torque ripple, efficiency, and dynamic motor performance.

? After completing this lecture, you will be able to:

• Compare different current sensing methods and their trade-offs.

• Understand the function of INA303 in accurate current measurement and protection.

• Analyze IGBT-based inverter hardware for PMSM drives.

• Relate hardware choices to torque control, noise reduction, and system safety.

In this lecture, you will dive deeper into the hardware design of sensorless PMSM drives, focusing on gate driver integration and MCU capabilities. You’ll analyze the UCC27714 high-side/low-side driver, bootstrap capacitor sizing for IGBTs, and the role of TI’s Piccolo F2802x MCU in enabling real-time motor control.

After completing this lecture, you will be able to:

• Explain the function of the UCC27714 gate driver and its impact on current sensing accuracy.

• Apply bootstrap capacitor sizing guidelines for IGBT-based PMSM inverters.

• Identify key MCU peripherals (PWM, ADC, comparators) used for real-time FOC control.

• Understand how hardware and MCU choices affect efficiency, stability, and protection in PMSM drives.