Model Order Reduction of Rotordynamical Systems

Model reduction of second order systems

where the matrix M ∈ RN×N is assumed to be invertible. Models of mechanical systems are often of this type since (1.1) then represents the equation of motion of the system. For such a system M = MT , C = CT and K = KT are respectively the mass, damping and stiffness matrices, f(t) ∈ RN×1 is the vector of external forces, and x(t) ∈ RN×1 is the vector of internal generalized coordinates (see [4]...

6 Model Reduction of Second - Order Systems

Model Order Reduction of Nonlinear Dynamical Systems

Model Order Reduction of Nonlinear Dynamical Systems by Chenjie Gu Doctor of Philosophy in Electrical Engineering and Computer Science University of California, Berkeley Professor Jaijeet Roychowdhury, Chair Higher-level representations (macromodels, reduced-order models) abstract away unnecessary implementation details and model only important system properties such as functionality. This meth...

Fast Model-order Reduction for Mechatronic Systems

We present recent advances in the mixed symbolic and numeric model reduction techniques for automatically extracting the dominant system behavior of multiphysical systems. A unique feature of our approach is to compute approximated symbolic formulas for linear and nonlinear system characteristics, rigorously reducing the complexity of symbolic expressions while controlling a user-given error bo...

Gramian-based model order reduction of parameterized time-delay systems

Time-delay systems (TDSs) frequently arise in circuit simulation especially in high-frequency applications. Model order reduction (MOR) techniques can be used to facilitate the simulation of TDSs. On the other hand, many kinds of variations, such as temperature and geometric uncertainties, can have significant impact on the transient responses of TDSs. Therefore, it is important to preserve par...