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Finite-Time Line-of-Sight Guidance-Based Path-Following Control for a Wire-Driven Robot Fish.

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Summary
This summary is machine-generated.

This study introduces an adaptive line-of-sight (LOS) guidance method with a finite-time sideslip angle observer for precise robotic fish path tracking. The method enhances yaw control for accurate planar trajectory following.

Keywords:
biomimetic robotic fishdirectional trackingline-of-sight guidance lawpath following

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Area of Science:

  • Robotics
  • Control Systems
  • Biomimetic Engineering

Background:

  • Robotic fish require precise path tracking for underwater tasks.
  • Sideslip angle significantly impacts trajectory accuracy.
  • Existing methods often struggle with real-time adaptation to dynamic conditions.

Purpose of the Study:

  • To develop an adaptive line-of-sight (LOS) guidance method for precise planar path tracking of a bionic robotic fish.
  • To mitigate the adverse effects of sideslip angle on tracking performance using a finite-time observer.
  • To validate the proposed control strategy through experimental evaluation.

Main Methods:

  • An adaptive LOS guidance method based on real-time cross-track error.
  • A finite-time observer (FTO) to estimate and correct time-varying sideslip angles.
  • Proportional-Integral-Derivative (PID) controllers for yaw tracking, integrated with a Central Pattern Generator (CPG) and an Inertial Measurement Unit (IMU).

Main Results:

  • The finite-time observer effectively observed and compensated for the sideslip angle.
  • The adaptive LOS guidance method demonstrated precise planar path tracking capabilities.
  • Experimental results validated the superior performance of the proposed method compared to baseline approaches.

Conclusions:

  • The proposed adaptive LOS guidance method with a finite-time sideslip observer significantly improves the planar path tracking accuracy of bionic robotic fish.
  • The integration of FTO and PID controllers offers a robust solution for real-time trajectory control in dynamic environments.
  • This approach provides a foundation for more sophisticated autonomous underwater vehicle control systems.