In this study, we are going to examining about microorganisms present in the environment influence the nature of populations affected by psychological disorders. For this objective, we have used two different dynamic systems where the first system is describing the dynamics of the psychologically suffering population, and the second system shows the environmental fluctuations due to the presence of microorganisms. In the Beginning, we coupled these systems through a synchronization procedure with active control. Our aim is to reduce dispersive interactions and find a way to achieve system stability. We are working on the development of a controller based on a genetic algorithm (GA) that provides adaptive tuning of synchronization parameters to improve performance in chaos management. In the final stage, we organizer large-scale numerical simulations for comparative analysis between the GA-based controller and the active control system. This results show that the GA-based controller is capable of achieving faster convergence, higher accuracy in synchronization, and achieving better resistaning response towards system disturbances. Thus, it has proven to be an effective technique for controlling chaos in such complex and dynamical environments.