Parameter Estimation of Loranz Chaotic Dynamic System UsingConstriction factor approach in Particle Swarm Optimization CFAPSO)

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 estimatedresponses 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 usingthe CFAPSO to solve this problem. Simulation results demonstrate the merit, effectiveness and robustness of CFAPSO Algorithm.

Keywords:

Loranz chaotic system , Parameter estimation CFAPSO Algorithm , Mean squared errors