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Simulation and Controller Design for a Fish Robot with Control Fins.

Sandhyarani Gumpina1, Seungyeon Lee2, Jeong-Hwan Kim2

  • 1Department of Aerospace Information Engineering, Konkuk University, Seoul 05029, Republic of Korea.

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Summary
This summary is machine-generated.

This study developed a fish robot simulation using MATLAB Simulink, creating linearized models for control design. Controllers designed for linear models effectively managed the nonlinear fish robot across various speeds.

Keywords:
PID controllerfish robotsix-degree-of-freedom equationsystem identification

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Fluid Dynamics

Background:

  • Developing effective control strategies for autonomous underwater vehicles (AUVs) like fish robots is crucial for marine exploration and research.
  • Fish robots present complex nonlinear dynamics due to hydrodynamic forces and fin interactions, making traditional control design challenging.

Purpose of the Study:

  • To design and validate a nonlinear simulation block for a fish robot in MATLAB Simulink.
  • To develop linearized models of the fish robot at different surge velocities for controller design.
  • To design and analyze proportional, integral, and derivative (PID) controllers based on the linearized models and assess their performance on the nonlinear system.

Main Methods:

  • A six-degree-of-freedom nonlinear simulation model was created, incorporating hydrodynamic forces and fin effects.
  • Linearized models were obtained using an identification tool by applying pseudo-random binary signal inputs to the nonlinear model at nominal surge velocities of 0.2, 0.4, and 0.6 m/s.
  • Two-degree-of-freedom PID controllers were designed using the linearized models, and their stability margins and bandwidths were analyzed.

Main Results:

  • PID controllers designed for the linearized models demonstrated robust performance when applied to the nonlinear fish robot simulation.
  • Analysis of controllers for the 0.4 m/s nominal surge velocity showed favorable gain and phase margins for surge, pitch, and yaw.
  • The study confirmed that a single controller designed for a linear model at 0.4 m/s could effectively control the nonlinear system across different surge velocities, with minimal overshoot and steady-state errors.

Conclusions:

  • Linear approximation models are effective for designing controllers for nonlinear fish robot systems.
  • Controllers designed based on linearized models exhibit good stability and performance when implemented on the nonlinear system.
  • The developed simulation and control strategy provide a viable approach for controlling fish robots in various operational conditions.