基于统一模型的离散时滞混沌系统的最优H∞状态估计

his paper is concerned with the problem of state estimation for a class of discrete-time chaotic systems with time delays. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these systems, such as chaotic neural networks, Chua's circuits, and Hénon map etc. Based on the H∞ performance analysis of this unified model using the linear matrix inequality (LMI) approach, H∞ state estimator are designed for this model with sensors to guarantee the asymptotic stability of the estimation error dynamic systems and to reduce the influence of noise on the estimation error. The parameters of these estimators are obtained by solving the eigenvalue problem (EVP). As most discrete-time chaotic systems with time delays can be transformed into this unified model, H∞ state estimator design for these systems can be done in a unified way. Two numerical examples are exploited to illustrate the effectiveness of the proposed estimator design schemes.