Data-Assisted Dynamic Modeling of Bionic Robotic Fish and Its Precise Speed Control

Jiarong Han, Shun Huang, Yingyu Yao, Zhongjing Ma*, Yu Liu, Suli Zou, Bo Yin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Dynamic modeling is essential for comprehending physical mechanisms and devising control strategies in bionic robot research. This letter introduces a novel dynamic modeling method that combines Lagrangian dynamics and data-assisted techniques for robotic fish with bionic morphology, multi-joint structures, and a flexible caudal fin. Firstly, a nonlinear continuous hydrodynamic model has been developed using extensive data derived from computational fluid dynamics (CFD), thereby capturing the high-fidelity locomotion of robotic fish. Secondly, based on mathematical derivation, a stability analysis method and controller design approach for biomimetic systems with periodic behaviors have been proposed. Furthermore, to demonstrate the model's efficacy, we designed a model reference adaptive controller for speed control. Both simulation and experimental results validate the model's accuracy, effectiveness, and potential for improving control consistency in tracking time-varying speeds of robotic fish.

Original languageEnglish
Pages (from-to)10447-10454
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume9
Issue number11
DOIs
Publication statusPublished - 2024

Keywords

  • Biologically-inspired robots
  • dynamics
  • hydrodynamic modeling
  • motion control
  • robotic fish

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Han, J., Huang, S., Yao, Y., Ma, Z., Liu, Y., Zou, S., & Yin, B. (2024). Data-Assisted Dynamic Modeling of Bionic Robotic Fish and Its Precise Speed Control. IEEE Robotics and Automation Letters, 9(11), 10447-10454. https://doi.org/10.1109/LRA.2024.3468176