Identification and Uncertainty Modeling for Multivariable Processes

The use of orthonormal functions and consistency relationships to identify models of multivariable processes and their uncertainty descriptions, is discussed in this paper. The norm-bounded uncertainty can be obtained from the covariance matrix of the parameters. Using a-priori consistency relationships, unstructured uncertainty may be converted to a structured one. The μ analysis shows that this uncertainty description is much less conservative.