Abstract
Reduced order modeling (ROM) is a very important technique for the analysis of high order systems. It is a technique of control theory, which examines properties of dynamical systems for reducing the complexity of large dimension systems, while preserving their input output relation. In this paper conventional methods of MOR for reducing higher order transfer functions (TF) are used and compared with artificial intelligence techniques. Then a comparative result is obtained which gives the time domain specifications. Conventional methods such as truncation method, V. Krishnamurthy and V. Seshadri approach and Dominant pole method are used. Artificial intelligence technique such as genetic algorithm (GA) which is an evolutionary technique is used. The results are simulated in MATLAB 2014.
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