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, and are suitable to engineers working with frequency-domain data. We also show that transfer functions that have similar magnitude or...[Show more]
|Collections||ANU Research Publications|
|Source:||International Journal of Robust and Nonlinear Control|
|01_Sandberg_Model_Approximation_using_2007.pdf||345.29 kB||Adobe PDF||Request a copy|
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