Abstract: “The authors present a combined method for order reduction of higher order linear dynamic systems using the advantages of the improved pole clustering and error minimization by PSO. The denominator of the reduced model is obtained by the improved pole clustering and PSO is employed for determining numerator coefficients by minimizing the integral square error between the transient responses of the original and reduced order models, pertaining to unit step input. The reduction procedure is simple, efficient and computer oriented. The proposed algorithm has been extended for the reduction of linear multivariable system. The algorithm is illustrated with the help of two numerical examples to highlight the advantages of the approach and the results are compared with the other existing techniques”

Keywords: Order Reduction, Pole Clustering, PSO, Relative mapping Errors, Stability