Adaptive Fuzzy Logic Control Framework for Aircraft Landing Gear Automation: Optimized Design, Real-Time Response, and Enhanced Safety - Dagal, Idriss; Mbasso, Wulfran Fendzi; Ambe, Harrison; Erol, Bilal; Jangir, Pradeep (SPRINGER, 2025)
The landing gear systems of aircraft are fundamental for the safety of flight operations, which include takeoffs, landings, and inflight operations. Nonetheless, conventional automation and control systems have difficulties with these tasks due to internal non-linear dynamics, external factors, and the complexity of coordinating all gear positions. This paper solves these problems by developing an optimized sequence control fuzzy logic controller (FLC) for the landing gears. With the use of a Mamdani-type fuzzy inference system (FIS), the work presented in this paper introduces novel control states of Transit and Locked that provide additional resilience and accommodation for the system. Optimization methods were used to improve the form of membership functions and refine rule bases to increase responsive decision-making. This research highlights the lack of fuzzy logic application in aviation subsystems by attempting to fill the gap of highly adaptive real-time operational and emergencies inadequately addressed in previous research. All the conducted simulations for different flight conditions, including hostile conditions and system failures, demonstrated a 25% improvement in the accuracy of transitions compared to the conventional systems and a 15% faster response time. Moreover, the system maintained functionality during mechanical malfunctions, suggesting that these new approaches may be leading toward true robustness and redundancy within the system. This micromachining strategy can be easily integrated with advanced optimization techniques and adaptive control schemes, significantly contributing to safety as well as efficiency in aerospace engineering. By focusing on the practical application of these advancements, this work leads to reliability and operational safety improvement in airline automation intelligence.
Keywords: Fuzzy logic control; Landing gear automation; Aircraft safety; Mamdani FIS; Flight phase management; SYSTEM; UAV; Engineering