LINEAR-SYSTEM IDENTIFICATION VIA AN ASYMPTOTICALLY STABLE OBSERVER

This paper presents a formulation for identification of linear multiva riable systems from single or multiple sets of input-output data. The system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded eigenvalue assignm ent procedure. The prescribed eigenvalues for the observer may be real , complex, mixed real and complex, or zero corresponding to a deadbeat observer. In this formulation, the Markov parameters of the observer are first identified from input-output data. The Markov parameters of the actual system are then recovered from those of the observer and us ed to realize a state space model of the system. The basic mathematica l formulation is derived, and numerical examples are presented to illu strate the proposed method.