趋同(经济学)
控制理论(社会学)
跟踪(教育)
控制器(灌溉)
弹道
水下
加速度
计算机科学
稳定性理论
滤波器(信号处理)
控制(管理)
自适应控制
理论(学习稳定性)
控制工程
工程类
人工智能
计算机视觉
非线性系统
心理学
地质学
农学
教育学
经济
生物
物理
机器学习
经济增长
海洋学
天文
量子力学
经典力学
作者
Hao Wang,Zizheng Wang,Jun Fu
出处
期刊:IEEE transactions on systems, man, and cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2022-11-14
卷期号:53 (5): 2726-2736
被引量:7
标识
DOI:10.1109/tsmc.2022.3218399
摘要
This work proposes a command filter-based adaptive practical prescribed-time (PPT) asymptotic tracking control scheme for autonomous underwater vehicles (AUVs) under dynamic uncertainties. Considering that the followers have limited communication angles in the leader–follower formation structure, where a novel controller is proposed to ensure communication angles to achieve preassignable precision within a predefined time. First, we present a PPT control for handling the limited communication angles and, thus, they are allowed to be limited, turnable, and controllable. Then, to achieve the asymptotic convergence of output tracking errors, the proposed adaptive controllers can effectively insure the trajectory tracking errors of AUVs asymptotically converge to zero under the influence of dynamic uncertainties. Furthermore, the derived asymptotically tracking command filter technique for AUVs not only deduce an acceleration-free strategy for followers but also achieve the asymptotic convergence of output tracking errors for the command filters themselves. In the end, the effectiveness of the proposed control strategy is demonstrated through stability analysis and simulation test.
科研通智能强力驱动
Strongly Powered by AbleSci AI