Dynamic simulation model of a biomimetic robotic fish with multi-joint propulsion mechanism

Author:

Korkmaz Deniz1,Akpolat Z. Hakan2,Soygüder Servet3,Alli Hasan3

Affiliation:

1. Department of Electronics and Computer Science, Fırat University, Elazig, Turkey

2. Department of Mechatronics Engineering, Fırat University, Elazig, Turkey

3. Department of Mechanical Engineering, Fırat University, Elazig, Turkey

Abstract

In this paper, a biomimetic carangiform robotic fish is analysed based on dynamic and kinematic models. The carangiform fish can swim with features like high mobility, fast swimming and changing direction suddenly. Because it has these amazing features, a carangiform swimmer is modelled. Dynamic and kinematic models are analytically obtained to design a biomimetic carangiform robotic fish. The designed robotic fish consists of two parts: an anterior rigid body and a flexible tail, which is modelled as a four-joint propulsion mechanism, and each joint is driven by a servo motor. The dynamic model is developed in the MATLAB/Simulink environment using a Lagrange function and the state-space model is performed to linearize the obtained model. Each joint is controlled with conventional PID controller in the simulation. Furthermore, a solid model of the robotic fish prototype is drawn in SolidWorks and transferred to the MATLAB/Simmechanics environment, and the motion of the robotic fish is simulated using joint angles. Finally, experimental studies and simulation results show that a carangiform motion for autonomous swimming is developed and verified using controlled joint angles.

Publisher

SAGE Publications

Subject

Instrumentation

Reference34 articles.

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards power cost analysis and optimization of a multi-flexible robotic fish;Ocean Engineering;2024-01

2. Genetic Algorithm Optimized Grey-Box Modelling and Fuzzy Logic Controller for Tail-Actuated Robotic Fish;Neural Processing Letters;2023-08-19

3. A Performance Optimization Strategy Based on Improved NSGA-II for a Flexible Robotic Fish;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

4. Real-time implementation of deep reinforcement learning controller for speed tracking of robotic fish through data-assisted modeling;Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science;2023-05-17

5. Toward Swimming Speed Optimization of a Multi-Flexible Robotic Fish With Low Cost of Transport;IEEE Transactions on Automation Science and Engineering;2023

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