Parameter estimation of unknown fractional-order memristor-based chaotic systems by a hybrid artificial bee colony algorithm combined with differential evolution

Abstract

In this paper, parameter estimation of unknown fractional-order memristor-based chaotic systems is concerned. Firstly, the parameter estimation is transformed into a multi-dimensional optimization problem, where the fractional orders are treated as independent variables. Then, a hybrid artificial bee colony algorithm combined with differential evolution and other searching mechanisms is put forward to solve the optimization problem. Finally, to demonstrate the effectiveness of the proposed method, numerical simulations based on two typical fractional-order memristor-based chaotic systems are conducted. The simulation results shows that the proposed approach for parameter estimation of unknown chaotic systems is a successful and promising method with higher calculation accuracy, faster convergence speed, and stronger robustness.