APPROXIMATION OF FEASIBLE PARAMETER SET IN WORST CASE IDENTIFICATION OF BLOCK-ORIENTED NONLINEAR MODELS

摘要

The estimation of the Feasible Parameter Set for block-oriented nonlinear models in a worst case setting is considered. A bounding procedure is determined both for polytopic and ellipsoidic sets, consisting in the projection of the FPS is contained in R~(MN) of the extended parameter vector onto suitable M or N-dimensional subspaces and in the solution of convex optimization problems which provide the extreme points of the Parameter Uncertainties Intervals of the model parameteres. Bounds obtained are tighter then in the previous approaches.