一类非线性系统状态的网络化估计方法

A Networked State Estimation Algorithm for a Class of Nonlinear Systems

提出了一类Lipschitz非线性连续时间时滞系统基于非均匀采样测量的网络化状态估计方法.利用线性连续时间系统采样控制的方法,在考虑系统和网络传输时滞及量化等因素的条件下,通过构造新的李雅普诺夫泛函得到了保证估计误差系统全局渐近稳定的线性矩阵不等式条件.在此基础上,给出了状态估计器增益矩阵基于线性矩阵不等式的计算方法.最后,通过仿真例子验证了本文方法的有效性.

This paper presents a new state estimation method for Lipschitz nonlinear continuous time delay systems subject to non-uniformly sampled measurements.Based on the recent developments in sampled-data control of linear continuous-time systems and with the consideration of system and transmission delay and data quantization,a new Lyapunov functional is constructed and a new linear matrix inequality sufficient condition is established to guarantee the global stability of the estimation error system.Then,a design method for the state observer gain matrix is obtained based on the linear matrix inequality approach.Finally,the effectiveness of the proposed state estimation algorithm is illustrated by a numerical example.