二部图
控制理论(社会学)
规范化(社会学)
非线性系统
航程(航空)
近似误差
人工神经网络
李雅普诺夫函数
计算机科学
观察员(物理)
数学
图形
算法
人工智能
控制(管理)
工程类
理论计算机科学
航空航天工程
社会学
物理
量子力学
人类学
作者
Yang Yang,Didi Chen,Qidong Liu,Sergey Gorbachev,Victor Kuzin
出处
期刊:IEEE Systems Journal
[Institute of Electrical and Electronics Engineers]
日期:2023-06-01
卷期号:17 (2): 1899-1908
标识
DOI:10.1109/jsyst.2022.3215853
摘要
Formation control is a hot topic in multiagent systems (MASs). In this article, a bipartite time-varying prescribed range formation is developed for a class of nonlinear MASs with unknown disturbances. The time-varying prescribed range formation means that agents achieve a formation shape within a predefined region relative to their neighbors, and the region changes along with the time-varying formation distance. An error transformation is introduced to transform this bipartite prescribed range formation problem into a stabilization control one. A surface-error-based predictor is developed to generate prediction errors for update of neural networks (NNs), and this form decouples approximation of system dynamics and control signal. With prescribed range information and signed graph, a disturbance observer with predictor-based NNs is constructed to compensate external disturbances and NNs' approximation errors. Also, a normalization learning method is employed to reduce the number of NN's learning parameters. With Lyapunov-based stability analysis, it is proven that a bipartite time-varying formation is achieved within a prescribed range. Simulation results with a group of quadrotors verify the effectiveness of the proposed bipartite control scheme.
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