Comparative analysis of techniques of order reduction for analysis of vehicle model

Abstract

It is essential to study the transfer function of the processes in-volved in any vehicle in order to know the behavioral study. As these are largeoperation processes and strenuous. In the light of this there is requirement toreduce the order of the vehicle’s transfer function so that it becomes convenientand easy to analyze various behavioral parameters such as steady state error,settling time, peak overshoot etc. During the process of order reduction of thesevehicle systems, it is desirable that the behavior of both original and reducedorder system remains identical. So these constraints should be kept in mind bythe researcher while designing and developing the model order reduction tech-niques to obtain the best possible approximation of the higher order system.This paper outlines hankel norm approximation, schur decomposition, normal-ized co-prime factor technique, balanced stochastic truncation techniques toreduce the order of a higher order system and then comparative study is un-dertaken for SISO and MIMO system by considering test examples on basis ofperformance parameters of time domain shown by step response behavior andfrequency domain shown by bode plot. The comparative analysis of all thetechniques is done to obtain the best technique out of the four techniques.