State Estimation of Time Varying Fractional Singular Systems

This paper presents a linear filtering for the stochastic fractional-order singular (FOS) models in discrete time varying (TV) cases. The filter is established by using deterministic argumentation in an entirely independent way besides the stochastic analysis, and the recursive algorithm is derived by solving a well-organized data-fitting estimate problem of complete state samples given the measurements for TV and noise correlated cases. By presenting a numerical simulation, we try to verify our hypothesis and results obtained throughout this paper.