Convergence and colored noise issues in bounding ellipsoid identification

摘要

The convergence and bias properties of a general class of optimal bounding ellipsoid (OBE) algorithms are discussed. OBE algorithms are set-membership (SM) based identification algorithms which are applied to models which are linear-in-parameters, and are closely related to weighted recursive least square error (WRLS) methods.