Hou Nan, Li Weijian, Song Yanhua, Chang Mengdi, Bu Xianye
Sanya Offshore Oil & Gas Research Institute, Northeast Petroleum University, Sanya 572025, China.
Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing 163318, China.
Sensors (Basel). 2025 May 2;25(9):2880. doi: 10.3390/s25092880.
This paper is dedicated to dealing with the design issue of a non-fragile state estimator for a type of nonlinear complex network subject to random couplings and random multiple time delays under binary encoding schemes (BESs). The BESs are put into use in the transmission of data from the sensor to the remote estimator. The phenomenon of bit errors is considered in the process of signal transmission, whose description utilizes a Bernoulli-distributed random sequence. The random couplings are represented by using the Kronecker delta function as well as a Markov chain. This paper aims to conduct a non-fragile state estimation such that, in the presence of some variations/perturbations in the gain parameter of the estimator, the estimation error dynamics will reach exponential ultimate boundedness in mean square and the ultimate bound will be minimized. Utilizing both stochastic analysis and matrix inequality processing, a sufficient condition is provided to guarantee that the constructed estimator satisfies the expected estimation performance, and the estimator gains are acquired by tackling an optimization issue constrained by some linear matrix inequalities. Eventually, two simulation examples are conducted, whose results verify that the approach to the design of a non-fragile estimator in this paper is effective.
本文致力于研究一种针对一类非线性复杂网络的非脆弱状态估计器的设计问题，该网络在二进制编码方案（BESs）下受到随机耦合和随机多重时滞的影响。BESs应用于从传感器到远程估计器的数据传输。在信号传输过程中考虑了误码现象，其描述采用伯努利分布随机序列。随机耦合通过克罗内克δ函数以及马尔可夫链来表示。本文旨在进行非脆弱状态估计，使得在估计器增益参数存在一些变化/扰动的情况下，估计误差动态在均方意义下达到指数最终有界性，并且最终界将被最小化。利用随机分析和矩阵不等式处理，提供了一个充分条件来保证所构造的估计器满足预期的估计性能，并且通过解决受一些线性矩阵不等式约束的优化问题来获得估计器增益。最后，进行了两个仿真例子，其结果验证了本文中设计非脆弱估计器的方法是有效的。
