INTERVAL SYSTEMS THEIR ORDER REDUCTION

Abstract

The works presented in the dissertation deals with new methods for model reduction of single input single output and multi input multi output linear interval systems as well as single input single output discrete interval systems in z-transfer function and comparison of result with already presented methods. Reduction of higher order system transfer function to low order models has been an important area in the control engineering environment for many years. In the model reduction , finding the low order model of given higher order system transfer function , which reflect the dominant characteristics of original system, normally step response matching are performed. Very few methods are available in literature for order reduction of Interval Systems. Bandhopadhyay done much work on Interval Systems, recently he presents two methods for continuous Interval Systems and one method for Discrete Interval Systems but it's not guarantee stability of reduced model. In this dissertation two methods for SISO Interval systems, one for MIMO Interval System and one for Discrete Interval System are proposed and their result compared by Bandhopadhyay and it yield good results. The advantages of the proposed methods are that characteristics of original system can be preserved in reduced models and the reduced models are always stable provided, the original system stable. In each methods general formulation, steps involved and reducing nth order system to rth order are explained with numerical examples