Design of optimized backstepping controller for the synchronization of chaotic Colpitts oscillator using shark smell algorithm
Incremental improvement in controller tuning for chaotic oscillator synchronization, a niche control systems problem.
The paper tunes an adaptive backstepping controller using the shark smell optimization algorithm to synchronize two chaotic Colpitts oscillators, achieving better accuracy and convergence compared to PSO-optimized and non-optimized controllers.
In this paper, an adaptive backstepping controller has been tuned to synchronize two chaotic Colpitts oscillators in a master slave configuration. The parameters of the controller are determined using shark smell optimization (SSO) algorithm. Numerical results are presented and compared with those of particle swarm optimization (PSO) algorithm. Simulation results show better performance in terms of accuracy and convergence for the proposed optimized method compared to PSO optimized controller or any non-optimized backstepping controller.