論文

2020年11月

Improvement of motion accuracy and energy consumption for industrial feed drive systems using adaptive sliding mode control

ISA Transactions
  • Abdallah Farrage
  • ,
  • Naoki Uchiyama

106
開始ページ
382
終了ページ
391
記述言語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.isatra.2020.06.025

© 2020 ISA Increasing of consumed energy is the dominating challenge in many industrial fields, especially in computer numerical controlled (CNC) machines. Therefore, reducing even a small amount of the consumed energy can lead to a significant reduction in the world's energy consumption. Control techniques, which are used to manufacture industrial parts using higher controller gains can generally enhance motion accuracy of feed drive systems; however they increase the energy consumption. This paper proposes a new adaptive sliding mode control (ASMC), in which energy saving and motion accuracy of industrial machines can be effectively enhanced. The adaptation strategy allows control gains to be adaptively updated based on tracking performance. Once the resultant errors increase due to disturbance, the control gains are simultaneously modified to generate adequate control signals and achieve the precise track to the desired reference. The proposed adaptive gains can be flexibly changed during reaching and sliding phases, and therefore motion accuracy and energy reduction are improved. In order to confirm the effectiveness, the proposed adaptive law was compared with different adaptation approaches in several previous studies using a circular motion trajectory. Experimental results show a significant enhancement on the motion accuracy and energy saving for the feed drives.

リンク情報
DOI
https://doi.org/10.1016/j.isatra.2020.06.025
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/32896386
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85090299491&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85090299491&origin=inward
ID情報
  • DOI : 10.1016/j.isatra.2020.06.025
  • ISSN : 0019-0578
  • PubMed ID : 32896386
  • SCOPUS ID : 85090299491

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