Receding horizon FIR filter with estimated horizon initial state and its application to aircraft engine systems

Proposes a version of the discrete-time receding horizon FIR filter (RHFF) using the estimated horizon initial state. The estimated horizon initial state is obtained from the best linear unbiased estimator (BLUE) scheme. The proposed RHFF for the current state can be represented in either an iterative form or a batch form. The proposed RHFF is always time-invariant and has unbiasedness and remarkable deadbeat properties. The proposed RHFF is shown to be equivalent to the existing RHFF with unknown horizon initial state. For the validity of the proposed RHFF, the problem of a third-order dynamic model of an F-404 aircraft engine system is considered via simulation studies.