先验与后验
计算机科学
人工神经网络
功能(生物学)
航程(航空)
常量(计算机编程)
控制(管理)
控制理论(社会学)
方案(数学)
领域(数学分析)
控制功能
控制工程
工程类
人工智能
数学
数学分析
哲学
认识论
进化生物学
生物
程序设计语言
航空航天工程
出处
期刊:Automatica
[Elsevier]
日期:2002-05-01
卷期号:38 (5): 910-912
被引量:85
标识
DOI:10.1016/s0005-1098(01)00272-2
摘要
This paper addresses the finite-time dynamic coverage problem for mobile sensor networks in unknown environments. By introducing a condition where dynamic coverage of all points within the sensing range of each sensor exceeds the desired coverage level by a positive constant, a switching control strategy is developed to guarantee the achievement of desired coverage of the whole mission domain in finite time. The environment is modeled by a density function and neural networks are introduced to learn the function. Due to the approximation capability of neural networks, the proposed control scheme can learn the environment without a priori knowledge on the structure of the density function.
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