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An Integrated Approach to Global Synchronization and State Estimation for Nonlinear Singularly Perturbed Complex Networks

机译:非线性奇摄动复杂网络全局同步与状态估计的集成方法

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摘要

This paper aims to establish a unified framework to handle both the exponential synchronization and state estimation problems for a class of nonlinear singularly perturbed complex networks (SPCNs). Each node in the SPCN comprises both “slow” and “fast” dynamics that reflects the singular perturbation behavior. General sector-like nonlinear function is employed to describe the nonlinearities existing in the network. All nodes in the SPCN have the same structures and properties. By utilizing a novel Lyapunov functional and the Kronecker product, it is shown that the addressed SPCN is synchronized if certain matrix inequalities are feasible. The state estimation problem is then studied for the same complex network, where the purpose is to design a state estimator to estimate the network states through available output measurements such that dynamics (both slow and fast) of the estimation error is guaranteed to be globally asymptotically stable. Again, a matrix inequality approach is developed for the state estimation problem. Two numerical examples are presented to verify the effectiveness and merits of the proposed synchronization scheme and state estimation formulation. It is worth mentioning that our main results are still valid even if the slow subsystems within the network are unstable.
机译:本文旨在建立一个统一的框架来处理一类非线性奇摄动复杂网络(SPCN)的指数同步和状态估计问题。 SPCN中的每个节点都包含“慢”和“快”动力学,它们反映了奇异的摄动行为。一般的类扇形非线性函数被用来描述网络中存在的非线性。 SPCN中的所有节点都具有相同的结构和属性。通过利用新颖的Lyapunov泛函和Kronecker乘积,表明如果某些矩阵不等式可行,则寻址的SPCN是同步的。然后针对同一复杂网络研究状态估计问题,其中目的是设计一个状态估计器,以通过可用的输出测量来估计网络状态,从而确保估计误差的动态(慢速和快速)是全局渐近的稳定。再次,针对状态估计问题开发了矩阵不等式方法。给出两个数值例子,以验证所提出的同步方案和状态估计公式的有效性和优点。值得一提的是,即使网络中速度较慢的子系统不稳定,我们的主要结果仍然有效。

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