控制工程
计算机科学
控制理论(社会学)
控制器(灌溉)
过程(计算)
跟踪误差
模糊逻辑
补偿(心理学)
车辆动力学
遥控水下航行器
工程类
控制(管理)
移动机器人
人工智能
机器人
生物
操作系统
汽车工程
心理学
精神分析
农学
作者
Lei Chen,Hongjing Liang,Yingnan Pan,Tieshan Li
标识
DOI:10.1109/taes.2023.3304283
摘要
In some crucial consensus tracking missions, the sign of the tracking error is not allowed to change during the tracking process. The existing tracking control schemes are unable to satisfy this requirement. To solve this issue, this work improves the conventional prescribed performance control (PPC) approach and applies it to the cooperative control of unmanned aircraft vehicle (UAV) systems. Moreover, the flight controller design incorporates human decision-making. This hybrid active interaction approach implies that humans and UAVs can execute complex and variable flight missions as a collaborative team. Considering that equipped motors are prone to faults when operating in harsh environments, this article presents an adaptive fuzzy fault compensation mechanism to ensure the flight safety of UAVs. Finally, the simulation study validates the effectiveness and control advantage of the proposed approach.
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