Novel Hybrid Optimization Algorithm for Parameter Estimation of Chaotic System

摘要

This paper proposes a novel hybrid optimization algorithm of Adaptive Cuckoo Search and Particle Swarm Optimization algorithm for parameter estimation of chaotic system. In order to enhance the accuracy and efficiency of ACS, the strategy of exploitation velocity adjustment via acceleration by distance of PSO algorithm is adopted. Thus, the algorithms mentioned above are used for estimation of the parameters of Lorenz chaotic system. Estimation result from each algorithm generates a standard deviation with the true parameter data, which is regarded as the fitness. Compared with ACS and PSO algorithm, the hybrid optimization algorithm is more efficient and accurate for parameter estimation, thus benefitting the simulation and control of chaotic systems.