The underactuated autonomous underwater vehicle (AUV) depth‐tracking approach is presented in this research along with comparative field experiments. First, a model‐free ADRC‐SMC pitch autopilot method is proposed to eliminate dynamics‐related disturbances. The active disturbance rejection control (ADRC) framework is adopted to compensate the complicated and unknown pitch dynamics into an approximate integral series type. Sliding mode control (SMC) feedback law is designed to further compensate for dynamic feedback linearization inaccuracy of the ADRC framework. Second, the disturbance rejection double‐loop depth‐tracking approach is suggested in conjunction with adaptive line‐of‐sight (ALOS), which converts depth tracking into pitch tracking. The ALOS not only estimates the actual angle of attack but also compensates the pitch‐tracking inaccuracy from the ADRC‐SMC in the inner loop. Then, the uniformly semiglobally exponential stability of the closed‐loop depth controller is proved after a detailed analysis of the stability from the inner loop to the outer loop. Finally, comparative field experiments are conducted to verify the proposed method. The effectiveness and strong disturbance rejection capabilities of the ADRC‐SMC pitch autopilot method and the suggested depth‐tracking approach are demonstrated by experimental results.

中文翻译：

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基于ADRC-SMC的欠驱动AUV抗扰深度跟踪控制

本研究提出了欠驱动自主水下航行器（AUV）深度跟踪方法以及现场对比实验。首先，提出了一种无模型 ADRC-SMC 俯仰自动驾驶仪方法来消除与动力学相关的干扰。采用自抗扰控制（ADRC）框架将复杂且未知的俯仰动态补偿为近似积分级数类型。滑模控制 (SMC) 反馈律旨在进一步补偿 ADRC 框架的动态反馈线性化误差。其次，建议将干扰抑制双环深度跟踪方法与自适应视线（ALOS）结合起来，将深度跟踪转换为俯仰跟踪。ALOS 不仅估计实际迎角，还补偿内环 ADRC-SMC 的俯仰跟踪误差。然后，通过详细分析内环到外环的稳定性，证明了闭环深度控制器的一致半全局指数稳定性。最后，通过现场对比实验验证了所提出的方法。实验结果证明了 ADRC-SMC 俯仰自动驾驶仪方法和建议的深度跟踪方法的有效性和强大的抗扰能力。