Model Order Reduction for Systems with Moving Loads

p(t)MOR: Time-Varying Parametric Model Order Reduction and Applications for Moving Loads

In this contribution we investigate Model Order Reduction (MOR) for linear systems with time-varying parameters p(t). Such systems arise, for instance, in structural dynamics and multibody simulations when the position of an acting force on the physical structure varies with time. This behaviour is found in many industrial applications, e.g. in meshing gears, milling processes, bridge cranes or...

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...

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...