Wu Xu, Jiang Guo-Ping, Wang Xinwei
School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Jiangsu Engineering Lab for IOT Intelligent Robots(IOTRobot), Nanjing 210023, China.
Entropy (Basel). 2019 Aug 15;21(8):797. doi: 10.3390/e21080797.
Model construction is a very fundamental and important issue in the field of complex dynamical networks. With the state-coupling complex dynamical network model proposed, many kinds of complex dynamical network models were introduced by considering various practical situations. In this paper, aiming at the data loss which may take place in the communication between any pair of directly connected nodes in a complex dynamical network, we propose a new discrete-time complex dynamical network model by constructing an auxiliary observer and choosing the observer states to compensate for the lost states in the coupling term. By employing Lyapunov stability theory and stochastic analysis, a sufficient condition is derived to guarantee the compensation values finally equal to the lost values, namely, the influence of data loss is finally eliminated in the proposed model. Moreover, we generalize the modeling method to output-coupling complex dynamical networks. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed model.
模型构建是复杂动态网络领域中一个非常基础且重要的问题。随着状态耦合复杂动态网络模型的提出,通过考虑各种实际情况引入了多种复杂动态网络模型。本文针对复杂动态网络中任意一对直接相连节点之间通信时可能发生的数据丢失问题,通过构建辅助观测器并选择观测器状态来补偿耦合项中丢失的状态,提出了一种新的离散时间复杂动态网络模型。利用李雅普诺夫稳定性理论和随机分析,推导出一个充分条件,以保证补偿值最终等于丢失值,即在提出的模型中最终消除数据丢失的影响。此外,我们将建模方法推广到输出耦合复杂动态网络。最后,给出两个数值例子来证明所提模型的有效性。