System identification in large scale systems with hierarchical structures

Abstract Due to its systems control orientation, the theory of multilevel hierarchical control developed by Mesarovic and others appears especially promising for identification and modeling of large scale systems consisting of relatively independent subsystems with strong and weak intersystem coupling. Standard techniques of optimum systems control and estimation theory may be used to resolve system problems described in this format. Determination of system structure and identification of system parameters form an inherent part of this procedure. To achieve advantages by hierarchical system concepts, it is necessary to decompose a large scale system into a number of smaller parts in such a manner that individual subsystem estimation, identification and control is feasible and to coordinate the subsystems in order to obtain the overall system goal. While decomposition is in theory easy, in practice it must be accomplished such that subsystem structure preserves constraints, information structures and acceptable authority structures. The success of coordination will thus, in practice, be affected by the particular system decomposition chosen. This paper presents the results of an investigation of system identification, using the maximum a posteriori criterion, of system parameters within a hierarchical structure. Examples demonstrate the use of the system identification algorithms.