Finite-time annular domain H2/H∞ filtering for mean-field stochastic systems with Wiener and Poisson noises

Abstract

This paper investigates the finite-time annular domain $H_2/H_{\infty }$ filtering for mean-field stochastic systems with external disturbance, Wiener and Poisson noises. Initially, the novel concept of finite-time annular domain (FTAD) $H_2/H_{\infty }$ filtering is introduced, which ensures the system’s mean square finite-time annular domain boundedness (MSFTADB) and minimizes the $H_2$ and $H_{\infty }$ filtering performance indices. Next, using the Itô-Levy formula and the reverse differential Gronwall inequality, a less conservative sufficient condition for the existence of finite-time annular domain $H_2/H_{\infty }$ filter is derived. Furthermore, a new algorithm is devised to establish the relationship between the ranges of adjustable parameters and the minimum value of $H_2$ performance index. Finally, a practical example is provided to verify the effectiveness of the proposed method.