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Self-tuning Control Method Based on Online Identification for Robot Servo System

  • Wangqiang Jia
  • , Ye Cao
  • , Jianfu Cao
  • Xi'an Jiaotong University

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

1 Scopus citations

Abstract

Changes in load parameters will affect the steady- state and transient-state performance of robot servo systems, so it is important to perform parameter self-tuning control methods for Proportional Integral (PI) controller. In this paper, a PI controller parameter self-tuning method based on frequent- domain and time-domain indexes for a permanent magnet synchronous motor (PMSM) servo system is proposed, and the Recursive Least Squares (RLS) algorithm with an identification switch is used to obtain the load inertia which is used to update self-tuning PI parameters in real time. The results of the simulation show that the algorithm proposed in this paper improves the system performance effectively.

Original languageEnglish
Title of host publicationProceedings - 2022 Chinese Automation Congress, CAC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3471-3476
Number of pages6
ISBN (Electronic)9781665465335
DOIs
StatePublished - 2022
Event2022 Chinese Automation Congress, CAC 2022 - Xiamen, China
Duration: 25 Nov 202227 Nov 2022

Publication series

NameProceedings - 2022 Chinese Automation Congress, CAC 2022
Volume2022-January

Conference

Conference2022 Chinese Automation Congress, CAC 2022
Country/TerritoryChina
CityXiamen
Period25/11/2227/11/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • PI controller parameter self-tuning
  • inertia identification
  • robot servo system
  • torque identification

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