The intrinsically reciprocating motion in fishlike propulsion causes severe attitude instability of a robotic fish, which poses enormous challenges for environmental perception and autonomous operation. To address this issue, in this article, we propose a reaction-wheel-based control framework for guaranteeing the roll stability of the robotic fish. The mechatronic design and dynamic model of the designed robotic fish with an internal rotor are presented. By means of the simplified model and frequency domain analysis, the effect factors about roll stability are concretely analyzed. More importantly, a hybrid controller that combines a sliding mode controller with a neural network feedforward compensator is developed to reject the severe disturbance on roll angle. Then, the Lyapunov stability theory is utilized to analyze the stability and convergence property of the closed-loop system. Finally, the experimental results show that the proposed methods possess more significant performances than the passive stabilization method, which provides a valuable reference for attitude stabilization control and robust environmental perception of underwater robots.

中文翻译：

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基于神经轮滑模控制的机器人鱼基于反应轮的侧倾稳定

鱼状推进中的内在往复运动引起机器人鱼的严重姿态不稳定性，这对环境感知和自主操作构成了巨大挑战。为了解决这个问题，在本文中，我们提出了一种基于反作用轮的控制框架，以保证机器人鱼的侧倾稳定性。介绍了带有内部转子的机器人鱼的机电设计和动力学模型。通过简化模型和频域分析，具体分析了横摇稳定性的影响因素。更重要的是，开发了一种将滑模控制器与神经网络前馈补偿器相结合的混合控制器，以消除严重的侧倾角干扰。然后，利用李雅普诺夫稳定性理论分析了闭环系统的稳定性和收敛性。最后，实验结果表明，所提出的方法比被动稳定方法具有更显着的性能，为水下机器人的姿态稳定控制和鲁棒的环境感知提供了有价值的参考。