欠驱动
控制理论(社会学)
跟踪(教育)
自动驾驶仪
扰动(地质)
内环
自抗扰控制
控制器(灌溉)
计算机科学
循环(图论)
控制工程
反馈线性化
控制(管理)
俯仰角
工程类
人工智能
生物
数学
非线性系统
物理
国家观察员
心理学
量子力学
教育学
古生物学
农学
组合数学
地球物理学
作者
Chuan Liu,Xianbo Xiang,Yu Duan,Lichun Yang,Shaolong Yang
摘要
Abstract 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI