ABSTRACT
In many engineering applications, processes are described by increasingly complex models that are difficult to analyze and difficult to control. Reduction of the order of the model may overcome some of these difficulties, but it is quite possible that model reduction incurs a significant loss of accuracy. Therefore, the system has to be analyzed in a manner that is useful for the application purpose. Simplification of the model based on this analysis usually results in a model of lower complexity which is easier to handle, and in a corresponding simplification of synthesis procedures for control and filtering problems. Furthermore, the simplification decreases the computational effort. Every application has its own demands, and different model reduction methods have different properties.
