Development of Double Closed loop Vector Control Using Model Predictive Control for Permanent Magnet Synchronous Motor

Also Available Domains AC Drives

Project Code :TEMACS59

Objective

The main objective of the proposed method is to get better dynamic response by tracking the current and resisting the load disturbance.

Abstract

Vector control has been widely used to manipulate the permanent magnet synchronous motor (PMSM), in which the traditional double proportional integral (PI) controllers have commonly been utilized. However, it is difficult to set the suitable parameters of PI and maintain the PMSM performance under the different operating regimes. In order to solve these problems, a double closed-loop model predictive control (MPC) strategy based on the vector control has been presented for PMSM in this paper. Firstly, a simplified discrete model of PMSM is established in the d-q coordinate system without considering the interference. Then, the MPC is developed to substitute the PI controller in the speed-loop and the q-axis current-loop, respectively, and a double closed-loop MPC control system is formed. Finally, some case studies are carried out. The simulation and experimental results demonstrate that the presented MPC strategy improves the dynamic and steady-state performance of PMSM


Keywords--Double closed-loop control Β· Model predictive control (MPC) Β· Permanent magnet synchronous motor (PMSM) Β· Vector control

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Block Diagram

Specifications

Software Configuration:

Operating System :  Windows 7/8/10

Application Software :  Matlab/Simulink

Hardware Configuration:

RAM :  8 GB

Processor :  I3 / I5(Mostly prefer)

Learning Outcomes

  • Introduction to Matlab/Simulink
  • What is EISPACK & LINPACK
  • How to start with MATLAB
  • About Matlab language
  • About tools & libraries
  • Application of Matlab/Simulink
  • About Matlab desktop
  • Features of Matlab/Simulink
  • Basics on Matlab/Simulink
  • Introduction to controllers.
  • Study of PWM techniques.
  • Project Development Skills:
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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