A stochastic analysis of robust estimation algorithms in H-infinity with rational basis functions

Abstract

In this paper, a two-stage nonlinear identification algorithm parameterized in terms of rational basis functions with fixed basis poles is studied when disturbances are subject to mild stochastic assumptions. The two-stage algorithm is the archetype for robust estimation algorithms in H-infinity and its first stage is linear-in-data. Conditions for the consistency of both the stages are derived. It is shown that the two-stage algorithm enjoys a better stochastic as well as deterministic performance than those of the linear algorithms. Copyright (C) 2001 John Wiley Sons, Ltd.