MIMO System Order Reduction Using Real-Coded Genetic Algorithm
Authors: Swadhin Ku. Mishra, Sidhartha Panda, Simanchala Padhy, C. Ardil
Abstract:
In this paper, real-coded genetic algorithm (RCGA) optimization technique has been applied for large-scale linear dynamic multi-input-multi-output (MIMO) system. The method is based on error minimization technique where the integral square error between the transient responses of original and reduced order models has been minimized by RCGA. The reduction procedure is simple computer oriented and the approach is comparable in quality with the other well-known reduction techniques. Also, the proposed method guarantees stability of the reduced model if the original high-order MIMO system is stable. The proposed approach of MIMO system order reduction is illustrated with the help of an example and the results are compared with the recently published other well-known reduction techniques to show its superiority.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1059443
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2261References:
[1] S. Mukherjee and R.N. Mishra,"Reduced order modelling of linear multivariable systems using an error minimization technique", Journalof Franklin Inst., Vol. 325, No. 2 , pp. 235-245,1998.
[2] S. S. Lamba, R. Gorez and B. Bandyopadhyay "New reduction technique by step error minimization for multivariable systems", Int. J. Systems Sci., Vol. 19, No. 6, pp. 999-1009,1988.
[3] R. Prasad, A. K. Mittal and S. P. Sharma " A mixed method for the reduction of multivariable systems", Journal of Institute of Engineers, India, IE(I) Journal-EL, Vol. 85, pp 177-181,2005.
[4] 4. C. Hwang " Mixed method of Routh and ISE criterion approaches for reduced order modelling of continuous time systems", Trans. ASME, J. Dyn. Syst. Meas. Control, Vol. 106,pp. 353-356. 1984.
[5] S. Mukherjee, and R.N. Mishra, "Order reduction of linear systems using an error minimization technique", Journalof Franklin Inst., Vol. 323, No. 1, pp. 23-32, 1987.
[6] N.N. Puri, and D.P. Lan, "Stable model reduction by impulse response error minimization using Mihailov criterion and Pade-s approximation", Trans. ASME, J. Dyn. Syst. Meas. Control, Vol. 110, pp. 389-394, 1988.
[7] P. Vilbe, and L.C. Calvez, "On order reduction of linear systems using an error minimization technique", Journal of Franklin Inst., Vol. 327, pp. 513-514, 1990.
[8] G.D. Howitt, and R. Luus, "Model reduction by minimization of integral square error performance indices", Journal of Franklin Inst., Vol. 327, pp. 343-357, 1990.
[9] Vishwakarma and Prasad, "MIMO System Reduction Using Modified Pole Clustering and Genetic Algorithm", Hindawi Pub. Corp. Mod. and Sim. in Engineering,
[10] G. Parmar, R. Prasad, and S. Mukherjee, "Order reduction of linear dynamic systems using stability equation method and GA," International Journal of Computer, Information, and Systems Science, and Engineering, vol. 1, no. 1, pp. 26-32, 2007.
[11] R. Prasad and J. Pal, "Use of continued fraction expansion for stable reduction of linearmultivariable systems," Journal of the Institution of Engineers, vol. 72, pp. 43-47, 1991.
[12] M. G. Safonov and R. Y. Chiang, "Model reduction for robust control: a schur relative errormethod," International Journal of Adaptive Control and Signal Processing, vol. 2, no. 4, pp. 259-272, 1988.
[13] R. Prasad, J. Pal, and A. K. Pant, "Multivariable system approximation using polynomial derivatives," Journal of the Institution of Engineers, vol. 76, pp. 186-188, 1995.