非线性系统
控制理论(社会学)
伯努利原理
上下界
计算机科学
协议(科学)
滤波器(信号处理)
国家(计算机科学)
事件(粒子物理)
伯努利分布
数学
算法
随机变量
工程类
人工智能
统计
数学分析
控制(管理)
替代医学
航空航天工程
病理
物理
医学
量子力学
计算机视觉
作者
Cong Huang,Peng Mei,Weiping Ding,Quan Shi,Qiuji Wu
摘要
Abstract This article is concerned with the resilient state‐saturated filtering issue for nonlinear complex networks via the event‐triggering protocol. The nonlinear inner coupling is taken into account, thereby better reflecting the nature of the complex networks. A set of Bernoulli‐distributed sequences are introduced to model the randomly occurring nonlinearities with a given probability. The signum function is utilized to characterize the state saturation owing to the physical limits on the system. For the purpose of energy saving, an event‐triggering protocol is adopted to govern the regulation of the transmission. The objective of this article is to develop an event‐triggering resilient filtering for nonlinear complex networks subject to state saturations as well as randomly occurring nonlinearities. By using matrix analysis techniques, we first guarantee the upper bound on the filtering error covariance by means of recursions and subsequently minimize such an upper bound by looking for the proper gain matrix relying on the solutions to two difference equations. Moreover, the performance evaluation of the designed filtering scheme is conducted by analyzing the boundedness of the estimation error in the mean square sense. Finally, an experimental example is exploited to validate the usefulness of the state‐saturated resilient filtering algorithm.
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