Fuzzy Neural Network algorithm based on the delay compensation force/position control structure of a redundant actuation parallel robot

Shuhuan Wen, Yanfang Zha, Haiyang Yu, Luigi Manfredi, Xiongfei Li, Sen Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a novel control method of the redundant force branch based on the force/position hybrid control structure of Smith predictor compensation is proposed. A fuzzy PI controller is designed based on Smith predictor compensation structure and it is included in the redundant force branch. This method can obtain good tracking and dynamic performance. However, fuzzy control doesn't have self-learning and adaptive ability, so fuzzy neural network (FNN) controller is used in the redundant force branch. The simulation results show that the proposed FNN algorithm based on delay compensation force/position hybrid control structure can improve the adaptability and the control accuracy of driving force of redundant branch.

Original languageEnglish
Title of host publication2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
PublisherIEEE
Pages142-147
Number of pages6
ISBN (Electronic)9781728155524
ISBN (Print)9781728155531
DOIs
Publication statusPublished - 16 Dec 2019
Event2nd World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2019 - Beijing, China
Duration: 21 Aug 2019 → …

Conference

Conference2nd World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2019
CountryChina
CityBeijing
Period21/08/19 → …

Keywords

  • control system synthesis
  • delays
  • force control
  • fuzzy control
  • fuzzy neural nets
  • mobile robots
  • neurocontrollers
  • PI control
  • position control
  • predictive control
  • robot dynamics

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  • Cite this

    Wen, S., Zha, Y., Yu, H., Manfredi, L., Li, X., & Wang, S. (2019). Fuzzy Neural Network algorithm based on the delay compensation force/position control structure of a redundant actuation parallel robot. In 2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA) (pp. 142-147). IEEE. https://doi.org/10.1109/WRC-SARA.2019.8931942