Fuzzy recovery controller for deep stall based on Particle Swarm Optimization

Deep stall is a prevailing flight condition which seriously threatens the safety of flight. Therefore, it's necessary to design an effective recovery controller to avoid accidents. In this paper, a fuzzy recovery controller is designed based on the Particle Swarm Optimization (PSO). In order to avoid tuning of parameters in the design of fuzzy controllers, the PSO algorithm is applied to optimize these parameters. Simulation results of aircraft models with different configuration indicate that the aircraft can recover from the deep-stall rapidly and smoothly. The algorithm shows strong adaptability to different configurations under which parameters may vary. Finally, a comparison of the algorithm in this paper and the dynamic recovery methods is given. The results show the superiority and the adaptability of the designed controller.