Model Reduction of Inhomogeneous Initial Conditions
نویسنده
چکیده
Our goal is to develop model reduction processes for linear dynamical systems with non-zero initial conditions. Standard model reduction schemes optimize system input/output characteristics but frequently destroy initial condition state space information. Additionally, existing model reduction schemes for initial conditions inappropriately assign weight to initial condition information. We propose a projectionbased model reduction scheme that combines subspaces from differing model reduction approaches and compare it to existing schemes. I. PROBLEM STATEMENT Given a LTI system with inhomogeneous initial conditions:
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