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Fuzzy Fault-Tolerant Following Control of Bionic Robotic Fish Based on Model Correction.

Yu Wang1, Jian Wang2, Huijie Dong3

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Summary
This summary is machine-generated.

This study introduces fault-tolerant control for bionic robotic fish using fuzzy logic and dynamic model correction. The method enables robotic fish to maintain following control despite joint failures, enhancing underwater operation capabilities.

Keywords:
bionic underwater robotfault-tolerant controlfuzzy controlmodel correction

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Area of Science:

  • Robotics
  • Control Systems
  • Marine Engineering

Background:

  • Bionic robotic fish face challenges in fault-tolerant control due to complex dynamics and joint failures.
  • Joint failures disrupt propulsion, affecting velocity and yaw performance, critical for navigation and task execution.

Purpose of the Study:

  • To develop a fault-tolerant following control framework for multi-joint bionic robotic fish.
  • To address control issues arising from joint failures using fuzzy control and dynamic model correction.

Main Methods:

  • Offline fault analysis to derive influence factor functions for joint faults.
  • Adaptive-period yaw filtering and improved line-of-sight navigation for motion accommodation.
  • Dual-loop fuzzy control strategy for coordinated velocity and yaw control.

Main Results:

  • The proposed framework effectively achieves fault-tolerant following control for bionic robotic fish.
  • Demonstrated robustness against multiple joint fault types through numerical simulations.
  • Influence factor functions accurately characterize fault impacts on fish performance.

Conclusions:

  • The developed fault-tolerant control strategy offers a viable solution for bionic robotic fish in complex underwater environments.
  • Fuzzy control methodologies combined with dynamic model correction enhance robotic fish resilience to failures.
  • This research contributes to reliable autonomous underwater operations.