Control and synchronization of chaotic systems with synergy of bacterial foraging and differential evolution algorithm

Control and synchronization of chaotic systems are studied. They are transformed into numerical optimization problems. A novel hybridization of differential evolution (DE) and bacterial foraging algorithm (BFOA), called CDEM algorithm, is proposed. The algorithm incorporates an adaptive chemotactic step from the BFOA into DE, which improves convergence of the classical DE. It introduces mutation operation of genetic algorithm for enhancing population diversity. Finally, CDEM algorithm is used to chaotic system control and synchronization. Numerical simulations based on Hénon Map demonstrate effectiveness and stability of the algorithm. Effects of parameters are investigated as well.