Precise Discrete-Time Steering Control for Robotic Fish Based on Data-Assisted Technique and Super-Twisting-Like Algorithm
Hai Wang, Chunlong Mi, Zhenwei Cao, Jinchuan Zheng, Zhihong Man, Xiaozheng Jin, Hao Tang
Abstract
In this article, a novel dynamic model of robotic fish with the data-assisted method is established and a discrete-time super-twisting-like controller (DTSTC) is proposed to effectively control the steering for a robotic fish. Although the thrust of the robotic fish is generated by the body motion in surrounding water environment, it is rather difficult to model the hydrodynamics in practice. Therefore, the data-assisted modeling method is applied where the reaction force generated by the yawing of fish head is also considered to obtain a more accurate model. The DTSTC is, then, designed to achieve robust steering control performance against system uncertainties. The experimental results are presented in support of the effectiveness and excellent performance of the proposed steering control scheme of the robotic fish.