Enhanced Satellite Synchronization Using Type-2 Asymmetric Fuzzy Brain Emotional Learning Control

This paper presents a novel approach for integrating synchronization techniques into chaotic satellite systems using type-2 fuzzy brain emotional learning control and asymmetric membership function. The proposed methodology aims to enhance the cognitive control capabilities of satellite systems, ensuring better adaptability and performance in dynamic and uncertain environments. The type-2 fuzzy brain emotional learning control system is designed to incorporate emotional learning mechanisms, enabling the satellite systems to make intelligent decisions and adapt their control strategies based on past experiences. By combining this emotional learning aspect with the asymmetric membership function, the control system gains the ability to handle uncertainties and imprecision in the system's inputs effectively. Furthermore, integrating self-organizing algorithms facilitates the automatic organization and adaptation of the control network structure, ensuring optimal system performance and scalability. To evaluate the effectiveness of the proposed approach, extensive simulations were conducted using representative scenarios of chaotic satellite systems. The results demonstrate the superiority of the type-2 fuzzy brain emotional learning control and asymmetric membership function integration, as it outperforms traditional control approaches regarding synchronization accuracy and robustness.