Improved Particle Swarm Optimization-Based Anti-Interference Control System for Aircraft - Zhang, Pengyu (2025 3rd International Conference on Data Science and Information System (ICDSIS), 2025)
This study discusses the design of an advanced Aircraft Anti-Interference Control System with an Improved Particle Swarm Optimization (IPSO) algorithm. The conventional control system tends to perform poorly against difficult electromagnetic and environment disturbances. Therefore, IPSO algorithm is used to adjust dynamically control parameters and improve adaptability of the system. The enhanced algorithm adjusts the inertia weight and implements adaptive learning strategies, allowing the swarm to converge more efficiently toward optimal solutions. Simulation results confirm that the IPSO-based system performs better than traditional PSO in stability, convergence rate, and robustness. The system is tested under different interference scenarios and exhibits dramatic improvements in sustaining flight path accuracy, control response and evaluated with performance metrics which has got an accuracy of 97.6%, 97.2% of precision, 97.1 of recall and 97.1% of F1-Score. Adaptability of the solution renders it appropriate for modern aircraft that is subject to constantly changing threats and environments. Using intelligent computation paired with real-time control, the system enhances the reliability of aircraft in mission-sensitive operations.