Bias Distribution in Continuous-Time Transfer Function Estimates by Prediction Error Method

Abstract

Estimation of simple transfer function models of complex dynamical systems is an important issue for robustness of all subsequent application stages of the models, such as control, fault detection etc. Here we consider an RLS approach to s-transfer function estimation based on prediction error minimization. An analysis of the algorithm determines the influence of the estimator design variables on the model bias distribution over frequency. A numerical example demonstrates this effect and provides guidelines for determining these to suit a given specification.