Abstrato

A Novel Method of Order Reduction for Interval System

Priya N., Dr.T K Sunilkumar

Modeling of physical systems usually results in complex high-order dynamic representation. The simulation and design of controller for high order system is complicated, since the cost and complexity of the controller increases with system order. Hence, it is desirable to approximate these models by reduced order model such that these low order models preserves all the salient features of its high-order model. A system with parameter variation within bound, creates interval in coefficient in the system polynomial and hence it is called interval system. This paper deals with model order reduction of single input single output linear time invariant interval systems. The method for model order reduction presented in this paper is based on approximate generalized time moments (AGTM) matching and optimization procedure. Luus –Jaakola optimization procedure is used for minimizing the performance index subject to the constraints. Using the order reduction technique describes here and the concept of model matching, a low order controller can be designed for interval systems. A numerical example is illustrated for showing the effectiveness of model order reduction method.