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

Abstract

AbstractIn 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∞ 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 © 2001 John Wiley & Sons, Ltd.