Published in the Proceedings of the 37th IEEE CDC, Tampa, December 1998

New Untuned Algorithms for Worst Case Identification

P. Date and G. Vinnicombe

Abstract

This paper considers the problem of approximating the given set of frequency response samples by an element from a particular, user specified subset of h-infinity. An untuned algorithm is suggested and a bound is established on the worst case identification error. It is shown that the worst case error is always bounded. Further, if the user specified subset includes the true plant set, the worst case error converges to zero as data becomes infinite and the noise goes to zero. Modified algorithms are proposed which minimise a particular worst case error bound. Finally, a simulation example demonstrates the use of the proposed algorithm.