EST

Call for paper
April Edition 2017

International Journal of Applied Information Systems solicits high quality original research papers for the
March 15, 2017
April 2017 Edition of the journal.
The last date of research paper submission is
March 15, 2017
SUBMIT YOUR PAPER

Number 5

Clustering Method for Reducing Order of Linear System using Factor Division Algorithm

journal image
  • International Journal of Applied Information Systems
  • Foundation of Computer Science (FCS), NY, USA
  • Volume 3 - Number 5
  • Year of Publication: 2012
  • Authors: Vinod Kumar, J. P. Tiwari
  • 10.5120/ijais12-450501
 Download
1639

Export

  • Vinod Kumar and J. P. Tiwari 2012. Clustering Method for Reducing Order of Linear System using Factor Division Algorithm. International Journal of Applied Information Systems. 3, 5 (July 2012), 1-4. DOI=http://dx.doi.org/10.5120/ijais450501 
  • @article{10.5120/ijais2017451568,
author = {Vinod Kumar and J. P. Tiwari},
title = {Clustering Method for Reducing Order of Linear System using Factor Division Algorithm},
journal = {International Journal of Applied Information Systems},
issue_date = {July 2012},
volume = {3},
number = {},
month = {July},
year = {2012},
issn = {},
pages = {1-4},
numpages = {},
url = {/archives/volume3/number5/225-0501},
doi = { 10.5120/ijais12-450501},
publisher = { xA9 2010 by IJAIS Journal},
address = {}
}

  • %1 450501
%A Vinod Kumar
%A J.  P.  Tiwari
%T Clustering Method for Reducing Order of Linear System using Factor Division Algorithm
%J International Journal of Applied Information Systems
%@ 
%V 3
%N 
%P 1-4
%D 2012
%I  xA9 2010 by IJAIS Journal

Abstract

A mixed method is proposed for finding stable reduced order models of single-input- single-output large-scale systems using Factor division algorithm and the clustering technique. The denominator polynomial of the reduced order model with respect to original model is determined by forming the clusters of the poles of the original system, and the coefficients of numerator polynomial with respect to original model are obtained by using the Factor division algorithm. The mixed methods are simple and guarantee the stability of the reduced model if the original system is stable. The methodology of the proposed method is illustrated with the help of examples from literature.

References

  1. S. K. Nagar, and S. K. Singh, An algorithmic approach for system decomposition and balanced realized model reduction, J. Franklin Inst. , Vol. 341, pp. 615-630, 2004.
  2. S. Mukherjee, Satakshi, and R. C. Mittal, Model order reduction using response matching technique,J. Franklin Inst. , Vol. 342, pp. 503-519, 2005.
  3. A. K. Mittal, R. Prasad, and S. P. Sharma, Reduction of linear dynamic systems using an error minimization technique, J. Inst. Eng. India IE(I) J. EL, Vol. 84, pp. 201-206, 2004.
  4. J. Hickin, Approximate aggregation for linear multivariable systems, Electronics letters, Vol. 16, No. 13, pp. 518-519, 1980.
  5. C. P. Therapos, Balanced minimal realization of SISO systems, Electronics letters, Vol. 19, No. 11, pp. 424-426, 1983.
  6. H. Sandberg, and A. Rontzer, Balanced truncation of linear time varying systems, IEEE Trans. Autom. Control Vol. 49, No. 2, pp. 217-229, 2004.
  7. P. Rozsa, and N. K. Sinha, Efficient algorithm for irreducible realization of a rational matrix, Int. J. Control, Vol. 21, pp. 273-284, 1974.
  8. G. Parmar, S. Mukherjee, and R. Prasad, Relative mapping errors of linear time invariant systems caused by particle swarm optimized reduced order model, Int. J. Computer, Information and systems science and Engineering,Vol. 1, No. 1, pp. 83-89, 2007.
  9. R. Prasad, S. P. Sharma, and A. K. Mittal, Improved Pade approximants for multivariable systems using stability equation method, Inst. Eng. India IE(I) J. EL ,Vol. 84, pp. 161-165, 2003.
  10. R. Prasad, S. P. Sharma, and A. K. Mittal, Linear model reduction using the advantages of mihailov criterion and factor division J. Inst. Eng. India IE(I) J. EL, Vol. 84, pp. 7-10, 2003.
  11. G. Parmar, S. Mukherjee, and R. Prasad, System reduction using factor division algorithm and eigen spectrum analysis, Int. J. Applied Math. Modeling,Vol. 31, pp. 2542-2552, 2007.
  12. T. C. Chen, C. Y. Chang and K. W. Han, Model reduction using the stability equation method and the continued fraction method, Int. J. control, Vol. 32, No. 1, pp. 81-94, 1980.
  13. G. Parmar, R. Prasad, and S. Mukherjee, Order Reduction of Linear Dynamic systems using Stability equation Method and GA J. Computer, Information and systems Sci. and Engg Vol. 1, pp. 26-32, 2007.
  14. A. K. Sinha, and J. Pal, Simulation based reduced order modeling using a clustering technique, Computer and Electrical Engg. , Vol. 16, No. 3, pp. 159-169, 1990.
  15. Lucas T. N. , Factor division: A useful algorithm in model reduction IEE Proc. Pt. D Vol. 130, No. 6, pp. 362-364, 1980.

Keywords

Clustering technique, Order reduction, Factor division algorithm, Transfer function, Stability, Integral square error (ISE)

Index Terms

Computer Science
Information Sciences