LINEAR SYSTEM REDUCTION FOR MULTI VARIABLE SYSTEMS

Abstract

It is a well established fact that the complexity of physical systems make their exact analysis a rather difficult and possibly a non-desirable task, mainly due to the difficult economic and computational consider.atio-ns -involved. This makes apparent the need for using model order reduction methods to obtain adequate reduced order model (s) which constitute a good approximation of the original system. In the last two decades many suitable reduction (or approximatiion) methods have been developed for high-order state-space models, or high-degree transfer functions of large-scale, linear, time-invariant, single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems. When the model reduction methods are applied to the state-space model formulatiion of the system they are called `time-domain order reduction methods', whereas when applied to the transfer function model formulation of the system they are called `frequency-domain order reduction methods' 1.2 Applications of Reduced