Li, BoShi, GuodongChen, XZhao, Q2024-02-16July 25-279789881563941http://hdl.handle.net/1885/313638In this paper, we investigate the capabilities of feedback mechanism in dealing with uncertainties for network systems. The study of maximum capability of feedback control was pioneered in Xie and Guo (2000) for scalar systems with nonparametric nonlinear uncertainty. In a network setting, nodes with unknown and nonlinear dynamics are interconnected through a directed interaction graph. Nodes can design feedback controls based on all available information, where the objective is to stabilize the network state. Using information structure and decision pattern as criteria, we specify three categories of network feedback laws, namely the global-knowledge/global-decision, network-flow/local-decision, and local-flow/local-decision feedback. We establish a series of network capacity characterizations for these three fundamental types of network control laws.This work is partially supported by National Natural Science Foundation of China (NSFC) under Grant 11301518 and the National Center for Mathematics and Interdisciplinary Sciences, CAS.application/pdfen-AU© 2018 IEEEadaptive controlnonlinear systemsfeedback mechanismnetwork systems201810.23919/ChiCC.2018.84832982022-10-02