Genetic algorithm for identification of time delay systems from step responses

Abstract

In this paper, a real-coded genetic algorithm is proposed for identification of time delay systems from step responses. FOPDT (First-Order Plus Dead-Time) and SOPDT (Second-Order Plus Dead-Time) systems, which are the most useful processes in this field, but are difficult for system identification because of a long dead-time problem and a model mismatch problem. Genetic algorithms have been successfully applied to a variety of complex optimization problems where other techniques have often failed. Thus, the modified crossover operator of a real-code genetic algorithm is proposed to effectively search the system parameters. The proposed method, using a real-coding genetic algorithm, shows better performance characteristics when compared to the usual area-based identification method and the directed identification method that uses step responses.