Model order reduction of S.I.S.O and M.I.M.O systems based on genetic algorithm

Abstract

The authors present an algorithm for order reduction of linear systems using the error minimization by Genetic algorithm (GA). The lower order transfer function are determined by minimizing the integral square error between the transient responses of original and reduced order models using Genetic algorithm. The reduction procedure is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Genetic Algorithm techniques guarantee stability of reduced order model if the original high order model is stable. the method illustrated through numerical example from literature and the results are compared with other model reduction techniques.