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Parameter identification of Lorenz chaotic system through Quantum Genetic Algorithm

Hongli Zhang, Haili Zhang

Abstract



Parameter estimation for chaotic systems is an important issue in nonlinear science which could be essentially formulated as a multidimensional optimization problem. For the accurate estimation of the unknown parameters of chaotic systems, puts forward the quantum genetic algorithm (QGA) is used to solve the optimization problem. The formulation of the parameter estimation as a nonlinear optimization problem to minimize the synchronization error of the observed state of the actual system and its mathematical model, benchmark function test shows that QGA's global search ability and reliability are improved greatly. Through a typical chaotic systems for numerical simulation of Lorenz equation and compared with QA and PSO show that whether it is in the speed and accuracy of identification of optimization have shown superiority. Quantum genetic algorithm is an efficient intelligent algorithm; the simulation results demonstrate the effectiveness of the proposed metho.

Keywords


Chaotic system; Parameter estimation; Quantum Genetic Algorithm; Lorenz chaotic system

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