Model approximation using magnitude and phase criteria: implications for model reduction and system identification


In this paper, we use convex optimization for model reduction and identification of transfer functions. Two different approximation criteria are studied. When the first criterion is used, magnitude functions are matched, and when the second criterion is used, phase functions are matched. The weighted error bounds have direct interpretation in a Bode diagram… (More)


7 Figures and Tables

Slides referencing similar topics