Reduced order surrogate modeling technique for linear dynamic systems

Reduced order linear anti-windup augmentation for stable linear systems

In this paper we provide algorithms based on Linear Matrix Inequalities for the design of fullauthority and external linear anti-windup compensators of reduced order guaranteeing finite global L2 gain. Previous results showed that the reduced order anti-windup design problem is non-convex. We propose here a convex approximation of the non-convex constraints leading to constructive design algori...

A data compression technique for PGD reduced-order modeling

This work concerns the Proper Generalized Decomposition (PGD), an a priori model reduction technique used to solve problems, eventually nonlinear, defined over the time-space domain. PGD seeks the solution of a problem in a reduced-order basis generated by a dedicated algorithm. This is the LATIN method, an iterative strategy which generates the approximations of the solution over the entire ti...

Reduced Order Modeling of Nonlinear Control Systems

Reduced order modeling of complex systems

Solutions of (nonlinear) complex systems are expensive with respect to both storage and CPU costs. As a result, it is difficult if not impossible to deal with a number of situations such as: continuation or homotopy methods for computing state solutions; parametric studies of state solutions; optimization and control problems (multiple state solutions); and feedback control settings (real-time ...

Reduced-Order Modeling of Time-Varying Systems

We present algorithms for reducing large circuits, described at SPICE-level detail, to much smaller ones with similar input–output behavior. A key feature of our method, called timevarying Padé (TVP), is that it is capable of reducing time-varying linear systems. This enables it to capture frequency-translation and sampling behavior, important in communication subsystems such as mixers and swit...