Model Free Reinforcement Learning based Control of Permanent Magnet Synchronous Motor Drive

Vikas, Pankaj Yadav, Bharat Singh, Rajesh Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Permanent Magnet Synchronous Motor (PMSM) drive plays a vital role in multiple applications, however, controlling of PMSM is a very complex task due to the presence of multiple nonlinear motor parameters which are directly dependent on its speed and current control mechanism. Traditional control algorithms such as vector control are badly impacted by these parameter variations. This research work presents the improved control topology under hybrid deep-reinforcement learning, which is more robust to changes in the motor parameters and loading conditions. Presented algorithm explicitly does not require the explicit plant model for tuning its parameters. Two control topologies based on the deep deterministic policy gradient (DDPG) algorithm and deep Q network (DQN) are proposed for controlling the PMSM. Additionally, the objective function based on the weighted sum of error of the tracking d-axis and q-axis current is proposed for learning control topology parameters. Numerous experimental investigations on the proposed current control of a drive have been carried out to demonstrate its effectiveness. The result shows that the DDPG is more reliable and has higher d-axis and q-axis current tracking accuracy as compared to the deep Q-learning algorithm.

Original languageEnglish
Title of host publication2023 International Conference on Computer, Electronics and Electrical Engineering and their Applications, IC2E3 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350338003
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event2023 International Conference on Computer, Electronics and Electrical Engineering and their Applications, IC2E3 2023 - Srinagar Garhwal, India
Duration: 8 Jun 20239 Jun 2023

Publication series

Name2023 International Conference on Computer, Electronics and Electrical Engineering and their Applications, IC2E3 2023

Conference

Conference2023 International Conference on Computer, Electronics and Electrical Engineering and their Applications, IC2E3 2023
Country/TerritoryIndia
CitySrinagar Garhwal
Period8/06/239/06/23

Keywords

  • Deep deterministic policy gradient (DDPG)
  • Deep Q network (DQN)
  • Model-free
  • Permanent magnet synchronous motor (PMSM)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Instrumentation

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