Preface Special Issue on “ Order Reduction of Large - Scale Systems ”

Order reduction is a common theme within the simulation, control, and optimization of complex physical processes. The mathematical models used in these computations often result in large-scale systems. For example, such systems arise due to accuracy requirements on the spatial discretization of fluids or structures, in the context of lumped-circuit approximations of distributed electronic circuit elements, such as the interconnect or package of VLSI chips, or in simulations of microelectromechanical systems (MEMS), which have both electrical and mechanical components. Order (or model, dimension) reduction is often crucial to accelerate the simulation of such large-scale systems. In fact, the systems may be so large that simulations or even storage of the data describing such systems are prohibitive without first replacing the original large-scale systems by suitably accurate reduced-order models of much smaller dimensions. This is even more evident if not only the simulation of the physical process is required, but control or optimization is the objective of the computation.