Model reduction and controller synthesis in the presence of parameter uncertainty
A system reduction theory based on matching output covariances and Markov parameters can be used to obtain reduced-order models that still contain parameter sensitivity information from the full order sensitivity model, and reduced-order controllers whose closed-loop performance is desensitized to variations in uncertain model parameters.
scientific article; zbMATH DE number 3950337
scientific article