A novel aircraft artificial fuzzy heuristic theory for nonlinear simulations

This paper presents a novel artificial fuzzy heuristic theory specifically designed for nonlinear simulations in the context of aircraft systems. Leveraging the principles of fuzzy logic, the proposed methodology addresses the complexities and uncertainties inherent in nonlinear dynamics of aircraft behavior. By integrating fuzzy inference systems with heuristic optimization techniques, we develop a robust framework that enhances the accuracy and efficiency of simulations. The study begins with a comprehensive review of existing methodologies in aircraft simulation, highlighting their limitations in handling nonlinearities and uncertainties. We then introduce our fuzzy heuristic approach, detailing its architecture and operational mechanisms. Through a series of simulations, we demonstrate the effectiveness of our theory in predicting aircraft performance under various operational scenarios. Results indicate significant improvements in simulation accuracy and computational efficiency compared to traditional methods. The proposed approach not only facilitates better understanding and analysis of aircraft dynamics but also provides a valuable tool for engineers and researchers in the field of aerospace engineering. Future work will explore the integration of this theory with real-time systems and its application in flight control design.