网络拓扑
控制理论(社会学)
非线性系统
滤波器(信号处理)
事件(粒子物理)
控制(管理)
计算机科学
拓扑(电路)
数学
物理
计算机网络
人工智能
组合数学
计算机视觉
量子力学
作者
Yonghua Peng,Guohuai Lin,Hongru Ren,Hongyi Li
摘要
Abstract This article investigates a formation control method for stochastic nonlinear multi‐agent systems (MASs) under switching topologies. To reduce the communication bandwidth occupancy, two event‐triggered mechanisms of sensor‐to‐controller and controller‐to‐actuator network channels are proposed. Taking advantage of the neural networks approximation capability, a dynamic high‐gain observer is introduced to estimate unmeasured states and tackle the non‐differentiable issue of triggered output signal. Furthermore, it should be noted that a distributed filter is employed to handle the discontinuous local reference signal resulting from switching topologies. By using discontinuous topology information, the distributed filter generates a differentiable signal to design a virtual controller. Concomitantly, a first‐order filter is implemented to avoid the problem of “explosion of complexity.” Through stability analysis, it is proven that the designed formation controller achieves boundedness in probability for all signals in the stochastic nonlinear MASs. Ultimately, a simulation is performed to confirm the viability of the control approach.
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