Reduced order modelling of linear multivariable systems using particle swarm optimisation technique. (23rd January 2008)

• Record Type: Journal Article
• Authors: Parmar, Girish; Mukherjee, Shaktidev; Prasad, Rajendra
• Is Part Of: International journal of innovative computing and applications. Volume 1:Number 2(2007)
• Page Start: 128
• Page End: 137
• Publication Date: 2008-01-23
• Subjects: dominant pole retention -- order reduction -- particle swarm optimisation -- PSO -- power systems -- reduced order modelling -- linear multivariable systems -- simulation; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

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 minimisation by Particle Swarm Optimisation (PSO) 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 minimising the Integral Square Error (ISE) in between the transient responses of original and reduced order models using PSO technique. The proposed algorithm guarantees stability of the reduced order transfer function matrix if the original High Order System (HOS) is stable and is having superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The proposed algorithm has been applied successfully to the transfer function matrix of a 10th 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.