Department of Electrical Engineering, Key Laboratory of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao, China
Xinbin Li
Department of Electrical Engineering, Key Laboratory of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao, China
Zhigang Lu
Department of Electrical Engineering, Key Laboratory of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao, China
Lichao Feng
College of Science, North China University of Science and Technology, Tangshan, China
Xianhui Meng
Department of Electrical Engineering, Key Laboratory of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao, China
Author (Mao, IEEE Trans. Autom. Control 2016) opens up the new chapter of discrete stochastic stabilization. In addition, intermittent control can reduce the control cost effectively. Inspired by the thoughts of discrete stochastic stabilization and periodically intermittent control, based on discrete observations of systems states, we can design periodically intermittent discrete time noises to almost surely exponentially stabilize an unstable differential system with the global Lipschitz condition using the methods of comparison principle and stochastic analysis. Up to now, this brief is the first to investigate the cross effects of discrete stochastic noises and periodically intermittent control for unstable differential systems, which can fill up with the gap of these two fields. Moreover, this brief applies the stabilization assertions to recurrent neural networks.
