Reduction of Second-Order Network Systems With Structure Preservation

Reduction of Second Order Systems Using Second Order Krylov Subspaces

By introducing the second order Krylov subspace, a method for the reduction of second order systems is proposed leading to a reduced system of the same structure. This generalization of Krylov subspace involves two matrices and some starting vectors and the reduced order model is found by applying a projection directly to the second order model without any conversion to state space. A numerical...

Modeling Dynamic Production Systems with Network Structure

This paper deals with the problem of optimizing two-stage structure decision making units (DMUs) where the activity and the performance of two-stage DMU in one period effect on its efficiency in the next period. To evaluate such systems the effect of activities in one period on ones in the next term must be considered. To do so, we propose a dynamic DEA approach to measure the performance of su...

Accuracy Enhanced Stability and Structure Preserving Model Reduction Technique for Dynamical Systems with Second Order Structure

A method for model reduction of dynamical systems with the second order structure is proposed in this paper. The proposed technique preserves the second order structure of the system, and also preserves the stability of the original systems. The method uses the controllability and observability gramians within the time interval to build the appropriate Petrov-Galerkin projection for dynamical s...

6 Model Reduction of Second - Order 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]...