Designing and generalizing of flight control gains using nearest neighbor algorithm

Purpose This study investigates the longitudinal control of aircraft by integrating classical feedback strategies with advanced feedforward and intelligent methods. The aim is to enhance system stability, minimize response time, and maintain robust performance under environmental uncertainties, contributing to safer and more efficient flight operations. Design/methodology/approach A hybrid control framework is developed that combines feedback, feedforward, and nearest-neighbor-based adaptive techniques. Detailed simulation and flight test analyses are conducted to evaluate system performance across a wide range of operating conditions, demonstrating improved disturbance rejection and trajectory tracking capabilities. Findings This paper provides a comprehensive analysis of various aircraft longitudinal control methods, using modern techniques combined with feedback and feedforward control strategies. The results demonstrate notable improvements in stability and dealing with uncertainties. This study aims to achieve optimal performance of longitudinal control systems by analyzing data in detail and comparing different methods. The findings indicate that the application of hybrid techniques can significantly enhance flight stability, reduce response times and address environmental uncertainties effectively. The outcomes of this research can serve as a guide for the development and improvement of control systems for the next generation of aircraft and pave the way for further research in this field. Originality/value This research presents a novel combination of traditional and intelligent control strategies for longitudinal aircraft dynamics, providing a practical methodology for real-time adaptive flight control. The findings offer guidance for future aircraft control system design and contribute to the advancement of intelligent flight technologies.