Published in the Proceedings of the European Control Conf., Karlsruhe, August 1999

Worst Case Identification Using FIR Models

P. Date and G. Vinnicombe

Keywords : worst case identification, nu-gap metric

Abstract

This paper considers a robustly convergent algorithm for worst case identification using FIR models. A new and stronger notion of robust convergence is established, and error bounds are obtained for a fixed model order as the length of data tends to infinity. The algorithm is shown to be implementable as a solution to an LMI optimisation problem. A robustly convergent algorithm for identification of plant coprime factors is suggested. An iterative technique for identification in the nugap metric is given. Two simulation examples demonstrate the use of these algorithms.