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Articles

Vol. 11 (2024)

Modeling and Control Experiments of a Fishtail-Like Pneumatic Soft Actuator

DOI
https://doi.org/10.31875/2409-9694.2024.11.12
Published
30.12.2024

Abstract

As the exploration of deep-sea resources continues, underwater actuators with conventional motors as the main building blocks can no longer meet the increasingly demanding needs. Inspired by bionics, researchers have started to work on underwater actuators with bionic structures. In this study, we designed and implemented a novel Fishtail-like Pneumatic Soft Actuator (FPSA). This innovative actuator configuration is inspired by the tail structure of Body and/or Caudal Fin (BCF) mode fish. The actuator's motion is achieved by controlling the expansion and contraction of the pneumatic soft muscles on both sides. And by constructing an experimental platform, we conducted an in-depth performance characterization, revealing the existence of a frequency-dependent nonlinear hysteresis characteristic of the FPSA. In order to accurately characterize this property, we built a dynamic model of the FPSA and successfully identified the uncertain parameters in the model by applying the nonlinear least squares method. The validation results show that the constructed model can accurately describe the nonlinear hysteresis characteristics of the FPSA. Finally, we successfully realized the high-precision trajectory tracking control of the endpoint of the FPSA using a PID controller. This result provides relevant ideas for the research of novel underwater bionic actuators.

References

  1. Zhang, Bingbing, et al. "Autonomous underwater vehicle navigation: a review." Ocean Engineering 273 (2023): 113861. https://doi.org/10.1016/j.oceaneng.2023.113861
  2. Bao, Haimo, et al. "A review of underwater vehicle motion stability." Ocean Engineering 287 (2023): 115735. https://doi.org/10.1016/j.oceaneng.2023.115735
  3. Wibisono, Arif, et al. "A survey on unmanned underwater vehicles: Challenges, enabling technologies, and future research directions." Sensors 23.17 (2023): 7321. https://doi.org/10.3390/s23177321
  4. Ahmed, Faheem, et al. "Survey on traditional and AI based estimation techniques for hydrodynamic coefficients of autonomous underwater vehicle." Ocean Engineering 268 (2023): 113300. https://doi.org/10.1016/j.oceaneng.2022.113300
  5. Chen, Gang, et al. "Swimming modeling and performance optimization of a fish-inspired underwater vehicle (FIUV)." Ocean Engineering 271 (2023): 113748. https://doi.org/10.1016/j.oceaneng.2023.113748
  6. Li, Zhihan, et al. "Development of a multi-tentacled collaborative underwater robot with adjustable roll angle for each tentacle." Ocean Engineering 308 (2024): 118376. https://doi.org/10.1016/j.oceaneng.2024.118376
  7. Fu, Jian, et al. "A unified switching dynamic modeling of multi-mode underwater vehicle." Ocean Engineering 278 (2023): 114359. https://doi.org/10.1016/j.oceaneng.2023.114359
  8. Cui, Zhongao, et al. "Review of research and control technology of underwater bionic robots." Intelligent Marine Technology and Systems 1.1 (2023): 7. https://doi.org/10.1007/s44295-023-00010-3
  9. Chen, Long, et al. "Research on underwater motion modeling and closed-loop control of bionic undulating fin robot." Ocean Engineering 299 (2024): 117400. https://doi.org/10.1016/j.oceaneng.2024.117400
  10. Ge, Liming, et al. "Design and analysis of wire-driven tail fin for bionic underwater glider." Ocean Engineering 286 (2023): 115460. https://doi.org/10.1016/j.oceaneng.2023.115460
  11. Li, Hanlin. "Bionic, Fin-propelled Underwater Multi-legged Robot." 2023 IEEE 3rd International Conference on Power, Electronics and Computer Applications (ICPECA). IEEE, 2023. https://doi.org/10.1109/ICPECA56706.2023.10075778