A CON: EVO Reduction Technique for Uncertain Interval Systems Using Differential Evolution Algorithm

Abstract

In this paper advantage of evolutionary technique is used in combination with a reliable conventional
technique to reduce the dimension of high order uncertain linear interval systems into low order interval
systems. The proposed technique is depicted by a name CON: EVO, which stands for combination of
conventional & evolutionary technique. In evolutionary method recently proposed Differential Evolution
(DE) optimization technique is used with and without powerful conventional Routh approximation technique
to minimize the integral square error (ISE) between transient responses of original higher order model and
reduced order model pertaining to a unit step input. The algorithm is simple, rugged and computer oriented.
It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state
value and stability of the original system. The proposed method is illustrated through a numerical example
and the results of proposed algorithms are compared with already presented Genetic algorithm method and
available Routh approximation conventional technique for interval system proposed by
Bandyopadhyay.
Keywords: Uncertain interval systems, Differential evolution, Reduced order modeling, Integral square
error.