SISO method using improved modified pole clustering and genetic algorithm

Author

Singh, Jay ; Vishwakarma, C.B. ; Chatterjee, Kalyan

Author_Institution

Dept. of Electr. Eng., Indian Sch. of Mines, Dhanbad, India

fYear

2015

fDate

27-28 March 2015

Firstpage

1

Lastpage

4

Abstract

To reduce the order of the large-scale dynamic systems, a method has been proposed by merging improved modified pole clustering and Genetic Algorithm. Reduced order denominator and numerator polynomial is obtained via improved modified pole clustering technique and Genetic Algorithm respectively. The method produces `k´ number of reduced order systems for k^th - order reduction. A numerical example has been taken from the literature to show the viability of the proposed mixed method and also compared with existing order reduction methods.

Keywords

genetic algorithms; large-scale systems; pattern clustering; poles and zeros; polynomials; reduced order systems; SISO method; genetic algorithm; improved modified pole clustering technique; k^th-order reduction method; large-scale dynamic systems; numerator polynomial; reduced order denominator; reduced order systems; Biological cells; Computational modeling; Computers; Electrical engineering; Genetic algorithms; Mathematical model; Polynomials; Genetic Algorithm; Improved modified pole clustering; Model order reduction; Stability; Transfer function;

fLanguage

English

Publisher

ieee

Conference_Titel

Energy Economics and Environment (ICEEE), 2015 International Conference on

Conference_Location

Noida

Print_ISBN

978-1-4673-7491-0

Type

conf

DOI

10.1109/EnergyEconomics.2015.7235117

Filename

7235117