Robust H Deconvolution and Its Application to Fault Detection

Abstract

The problem of H∞ deconvolution of linear discrete-time stationary processes is considered where the parameters of the process are partially unknown. By the use of the state-space model of the system, the state-space matrices are assumed to reside in a given polytope. A stationary deconvolver is obtained that achieves a preassigned input estimation level for all of the matrices in the uncertainty polytope. Two types of deconvolvers are considered: The first one directly aims at estimating the selected inputs, whereas the second type tries to estimate a dynamically weighted version of the input. The theory presented is illustrated via an example of fault detection in a servosystem of an air vehicle.