Reduced Order Modelling of Linear Mimo Systems Using Genetic Algorithm

In this paper, an algorithm for order reduction of linear multivariable systems is proposed using the combined advantages of the dominant pole retention method and the error minimization by Genetic algorithm. 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 Genetic algorithm. Each element of the transfer function matrix of the original system is considered separately. The reduction procedure is simple and computer oriented. The proposed algorithm guarantees stability of the reduced order transfer function matrix if the original high order system is stable and is having superior features, including easy implementation and good computational efficiency. The proposed algorithm has been applied successfully to the transfer function matrix of a 10 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. (Received in November 2006, accepted in May 2007. This paper was with the authors 1 month for 1 revision.)