Identification, structure selection and validation of uncertain models with set-membership error description

This paper discusses the problem of parameter identification in presence of errors and uncertainties characterized by a set-membership description. Some relations existing between posterior identifiability, structure selection and validation, and the influence of modeling and measurement error are pointed out. Both theoretical and algorithmic problems are discussed; special attention is devoted to the influence of various assumptions and a priori information on the algorithmic complexity. Finally a practical example, derived from the tuning procedure of a digital voltmeter in an intelligent measurement equipment, is presented.