An intelligent controller of homo-structured chaotic systems under noisy conditions and applications in image encryption

Due to the maturation of research on chaos and secure communication, the control technology of nonlinear systems, specifically chaos synchronization, has captured the attention of numerous researchers. Focusing on the issues of inflexibility in the design of chaotic synchronization controllers, the need for prior synchronization of the target system structure, and noise's disruptive impact on synchronization, this paper presents solutions that enhance the practical application of chaos. Firstly, the RBF neural controller is adjusted in this paper to bolster the control precision of the chaotic system and enhance its resilience to external disturbances. Secondly, this article presents an enhanced PSO optimization algorithm for the improved RBF neural controller to improve the optimization efficiency of the controller parameters. Finally, the simulation results of the Lorenz system validate the feasibility of the proposed synchronization control scheme. Additionally, the use of chaotic synchronization in image encryption demonstrates that synchronization accuracy can fulfill the requirements of image encryption application scenarios. •The structure of the RBF neural controller is improved to achieve better synchronization control performance, including synchronization accuracy and noise resistance.•The PSO algorithm is improved specifically for the intelligent chaotic controller studied in this article to enhance the efficiency of searching for RBF controller parameters.•Reduce the number of controllers used for synchronizing, improve the robustness of the synchronization system to noise, and a flexible and straightforward chaotic synchronization controller design.