A new model order reduction technique for the reduction of the linear time invariant system has been proposed in this paper. An improved clustering algorithm is employed in the proposed method to obtain the reduced order denominator polynomial. The reduced order numerator polynomial is obtained with a simple mathematical calculation as mentioned in the proposed scenario. The validity of the proposed method has been illustrated through some numerical examples. The improved clustering algorithm guaranteed the stability in the reduced model and also preserves the characteristics of the original system in the approximated one. The method is extended to the higher order multivariable system described by its matrix transfer function.
BistritzYShakedU (1984) Minimal Pade model reduction for multivariable systems. Journal of Dynamic systems, Measurement and Control106(4): 293–299.
3.
ChenTCChangCYHanKW (1979) Reduction of transfer functions by the stability-equation method. Journal of Franklin Institute308(4): 389–404.
4.
ChenTCChangCYHanKW (1980a) Model reduction using stability equation method and the Pade approximation method. Journal of Franklin Institute309: 473–490.
5.
ChenTCChangCYHanKW (1980b) Model reduction using stability equation method and continued fraction method. International Journal of Control32(1): 81–94.
6.
7.
GutmanPOMannerfeltCFMolanderP (1982) Contributions to the model reduction problems. IEEE Transactions on Automatic Control27(2): 454–455.
8.
HowittGDLuusR (1990) Model reduction by minimization of integral square error performance indices. Journal of Franklin Institute327: 343–357.
9.
HwangC (1984) Mixed method of Routh and ISE criterion approaches for reduced order modelling of continuous time systems. ASME Journal of Dynamic Systems, Measurement, and Control106: 353–356.
10.
KrishnamurthyVSeshadriV (1978) Model reduction using the Routh stability criterion. IEEE Transactions on Automatic Control23: 729–731.
11.
LalMMitraR (1974) Simplification of large scale system dynamics using a moment evaluation algorithm. IEEE Transactions on Automatic Control19: 602–603.
12.
LambaSSGorezRBandyopadhyayB (1988) New reduction technique by step error minimization for multivariable systems. International Journal of Systems Science19(6): 999–1009.
13.
14.
15.
ManigandanTDevarajanNSivanandamSN (2005) Design of PID controller using reduced order model. Academic Open Internet Journal15.
16.
MittalAKPrasadRSharmaSP (2004) Reduction of linear dynamic systems using an error minimization technique. Journal of Institution of Engineers IE (I)84: 201–206.
17.
18.
MukherjeeSMishraRN (1987) Order reduction of linear systems using an error minimization technique. Journal of Franklin Institute323(1): 23–32.
19.
MukherjeeSMishraRN (1988) Reduced order modeling of linear multivariable systems using an error minimization technique. Journal of Franklin Institute325(2): 235–245.
20.
PalJ (1979) Stable reduced order Pade approximants using the Routh Hurwitz array. Electronic Letters15(8): 225–226.
PalJSinhaAKSinhaNK (1995) Reduced-order modelling using pole clustering and time-moment matching. Journal of the Institution of Engineers (India)76: 1–6.
23.
24.
ParmarGPrasadRMukherjeeS (2007) Order reduction of linear dynamic systems using stability equation method and GA. International Journal of Computer, Information, and Systems Science, and Engineering1(1): 26–32.
25.
26.
PrasadRVishwakarmaCB (2009) Linear model order reduction using Mihailov criterion and Cauer second form. Journal of Institution of Engineers (India) – Electronic Letters90: 18–21.
27.
PrasadRSharmaSPMittalAK (2003) Linear model reduction using the advantages of Mihailov criterion and factor division. Journal of the Institution of Engineers (India)84: 7–10.
28.
PuriNNLanDP (1988) Stable model reduction by impulse response error minimization using Mihailov criterion and Pade’s approximation. ASME Journal of Dynamic Systems, Measurement, and Control110: 389–394.
29.
RamarKRamaswamyB (1968) Transformation to the phase variable canonical form. IEEE Transactions on Automatic Control13: 746–747.
30.
ShamashY (1975) Model reduction using the Routh stability criterion and the Pade approximation technique. International Journal of Control21(3): 475–484.
31.
ShiehLSWeiYJ (1975) A mixed method for multivariable system reduction. IEEE Transactions on Automatic Control20: 429–432.
32.
33.
VilbePCalvezLC (1990) On order reduction of linear systems using an error minimization technique. Journal of Franklin Institute327: 513–514.
34.
VishwakarmaCBPrasadR (2008) Clustering method for reducing the order of linear system using a Pade approximation. Institution of Electronics and Telecommunication Engineers (IETE) Journal of Research54(5): 326–330.
35.
36.
Wan Bai-Wu (1981) Linear model reduction using Mihailov criterion and Pade approximation technique. International Journal of Control33(6): 1073–1073.
