针对水下机器人（ROV）抗强干扰能力差和易产生抖振等问题，提出一种基于自抗扰控制（ADRC）的非线性光滑曲线cfal以改进扩张状态观测器（ESO）并用于水下机器人姿态控制。首先，建立基于偏航角控制的ROV动力学模型；然后，利用二次函数特征构造一种非线性分段函数cfal用以弥补常规fal函数的缺陷，进一步满足曲线选取的条件，从而降低系统的抗干扰能力并利用李雅普诺夫函数对改进ESO进行稳定性验证；最后，通过仿真实验结果得出，与经典自抗扰控制技术相比，在减少抖振加快响应速率的同时，ROV在分别面对突发干扰、正弦干扰、白噪声干扰以及综合干扰时，其对应的相关区间均方误差分别下降了10.6%，9.2%，16.0%，9.3%。
To address the issues of poor anti-disturbance capability and susceptibility to chattering in remote operated vehicle (ROV) attitude control, a nonlinear smooth function cfal based on active disturbance rejection control (ADRC) is proposed to improve the extended state observer (ESO). First, a dynamic model of the ROV based on yaw angle control is established. Then, leveraging the characteristics of a quadratic function, a nonlinear piecewise function cfal is constructed to overcome the shortcomings of the conventional fal function and better satisfy curve selection conditions, enhancing anti-disturbance capability and verifying the stability of the improved ESO using the Lyapunov function. Simulation results show that compared to classical ADRC, the proposed method reduces chattering, accelerates response speed, and decreases the mean squared error (MSE) by 10.6%, 9.2%, 16.0%, and 9.3% under sudden disturbances, sinusoidal disturbances, white noise disturbances, and composite disturbances, respectively.
2025,47(16): 100-106 收稿日期：2024-11-18
DOI：10.3404/j.issn.1672-7649.2025.16.015
分类号：U66；TP273
基金项目：国家自然科学基金资助项目（62363013）；江西省教育厅科学技术重点研究项目（GJJ2200805）；江西省自然科学基金资助项目（20224BAB202036）；江西理工大学研究生创新计划资助项目（XY2023-S208）
作者简介：鄢化彪(1978-),男,硕士,副教授,研究方向为复杂系统建模及深度学习
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