Linear multivariable system reduction using particle swarm optimization and a comparative study using relative integral square error

Abstract

An algorithm for order reduction of linear multivariable systems has been presented using the combined advantages of the dominant pole retention method and the error minimization by particle swarm optimization technique. The denominator of the reduced order transfer function matrix is obtained by retaining the dominant poles of the original system while the numerator terms of the lower order transfer matrix are determined by minimizing the integral square error in between the transient responses of original and reduced order models using particle swarm optimization technique. The reduction procedure is simple and computer oriented.The proposed algorithm has been applied successfully to the transfer function matrix of a 10 th order two-input two-output linear time invariant model of a practical power system. The performance of the algorithm is tested by comparing the relevant computer simulation results. © 2010 Springer-Verlag Berlin Heidelberg.