Optimized Cooperative Control of Error Port-Controlled Hamiltonian and Adaptive Backstepping Sliding Mode for a Multi-Joint Industrial Robot

Authors

Xiaoyu Yang, Haisheng Yu

Abstract

Robot joints driven by permanent magnet synchronous motors (PMSM) often cannot have both superior accuracy and rapidity when they track target signals. The robot joints have fine dynamic characteristics and poor steady-state characteristics when the signal controller is used, or they have fine steady-state characteristics and poor dynamic characteristics when the energy controller is used. It is hard to make robot joints that have both superior dynamic and steady-state characteristics at once using a single control method. In order to solve this problem, the strategy of optimized cooperative control is proposed. First, an error port-controlled Hamiltonian (EPCH) energy controller and an adaptive backstepping sliding mode (ABSM) signal controller are designed. Second, an optimized cooperative control coefficient based on the position error of a robot joint is designed; this enables the system to switch smoothly between the EPCH energy controller and ABSM signal controller. Next, the strategy of optimized cooperative control is designed. In this way, robot systems can combine the advantages of the EPCH energy controller and the ABSM signal controller. Finally, simulation results demonstrate that using the strategy of optimized cooperative control gives robot joints outstanding control performance in terms of tracking accuracy and response rapidity.

Citation

• Journal: Mathematics
• Year: 2023
• Volume: 11
• Issue: 6
• Pages: 1542
• Publisher: MDPI AG
• DOI: 10.3390/math11061542

BibTeX

@article{Yang_2023,
  title={{Optimized Cooperative Control of Error Port-Controlled Hamiltonian and Adaptive Backstepping Sliding Mode for a Multi-Joint Industrial Robot}},
  volume={11},
  ISSN={2227-7390},
  DOI={10.3390/math11061542},
  number={6},
  journal={Mathematics},
  publisher={MDPI AG},
  author={Yang, Xiaoyu and Yu, Haisheng},
  year={2023},
  pages={1542}
}

Download the bib file

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