%0 Journal Article
%T Parameter Estimation of Loranz Chaotic Dynamic System Using Constriction factor approach in Particle Swarm Optimization (CFAPSO)
%A Reza Gholipour
%A Alireza Khosravi
%A Zahra Rahmani
%A Jalil Addeh
%J International Journal of Mechatronics, Electrical and Computer Technology
%D 2012
%I Austrian E-Journals of Universal Scientific Organization
%X An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Constriction factor approach in particle swarm optimization (CFAPSO) is a new member of meta-heuristics. This paper focuses on using the CFAPSO to solve this problem. Simulation results demonstrate the merit, effectiveness and robustness of CFAPSO Algorithm.
%K Loranz chaotic system
%K Parameter estimation
%K CFAPSO Algorithm
%K Mean squared errors
%U http://aeuso.org/Vol.2/Vol.2%284%29,%20Jul,%202012/Parameter%20Estimation%20of%20Loranz%20Chaotic%20Dynamic%20System%20Using%20Constriction%20factor%20approach%20in%20Particle%20Swarm%20Optimization%20%28CFAPSO%29.pdf