Many systems that arise in practice are complex in nature and of a higher-order. The mathematical procedures of modeling such systems lead to a comprehensive description of the process in the form of complex, higher-order transfer functions or state-space models. This complexity often makes it difficult to obtain a good understanding of the behavior of the system. Therefore, higher-order models are difficult to use for simulation, analysis or controller synthesis, and it is not only desirable, but often necessary to obtain satisfactory reduced-order representations of such higher-order models. The main objective of model order reduction is to obtain a reduced-order approximate of a complex higher-order system that retains and reflects the important characteristics of the original system as closely as possible.