Title :
Real coded Integer Genetic Algorithm for parameter identification of non linear system
Author :
Megherbi, A.C. ; Megherbi, H. ; Dendouga, A. ; Benmahammed, K. ; Aissaoui, A.
Author_Institution :
Dept. of Electr. Eng., Univ. Mohamed Khider, Biskra, Algeria
Abstract :
In this paper, a real coded Integer Genetic-Algorithm (RCIGA) was developed to identify the parameters of non-linear systems and was successfully applied with acceptable accuracy. This algorithm can achieve robustness and efficiency in identifying parameters of non-linear systems. The genetic algorithm (GA) in ordinary form is a binary encoding during the operating procedures of optimization. In the real application, the real-coded GA has a wide variety of applications. This two types of GA procedures suffers for the loss of precision. Thus in this work we utilize a new concept of chromosome (encoding real coded Integer) to identifie the parameters of induction motor (IM) as an example of the non linear system. Simulation results show that the parameters identification based RCIGA is feasible and gives high precision.
Keywords :
genetic algorithms; nonlinear systems; parameter estimation; RCIGA; nonlinear system; parameter identification; real coded integer genetic algorithm; Biological cells; Encoding; Genetic algorithms; Induction motors; Mathematical model; Parameter estimation; Rotors; chromosome encoding; genetic algorithm; induction moto; nonlinear system; parameter identification;
Conference_Titel :
Communications, Computing and Control Applications (CCCA), 2011 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4244-9795-9
DOI :
10.1109/CCCA.2011.6031502