Portal de Periódicos da CAPES

Hybrid fuzzy logic flight controller synthesis via pilot modeling

1995; American Institute of Aeronautics and Astronautics; Volume: 18; Issue: 5 Linguagem: Inglês

10.2514/3.21510

1533-3884

Kalmanje Krishnakumar, Paul Gonsalves, A. Satyadas, Greg L. Zacharias,

Control Systems and Identification

This paper presents an investigation of a hybrid technique developed for synthesizing fuzzy logic controllers as stability augmentation systems. The hybrid technique combines the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms, to yield a fuzzy logic controller augmentation system optimized to satisfy desired handling qualities requirements. An optimal control model is used to provide the closed-loop handling qualities metrics. The optimal control model is an analytic model of the pilot which can support the computation of in-flight handling qualities metrics, such as the standard Cooper-Harper rating. A genetic algorithm is used to optimize the attributes of the fuzzy logic controller. These attributes include the parameters of the fuzzy logic controller membership functions and the rule structure. The hybrid technique was implemented and tested in an offline engineering simulation using a wide-envelope F/A-18 longitudinal model. The tests included examining the robustness of the fuzzy logic controllers, the robustness of the genetic algorithms optimization technique, and the effect of changing the number of rules used in the fuzzy logic controller. Results indicate that the approach provides a robust design technique for fuzzy logic controller stability augmentation system synthesis and also show that the synthesized fuzzy logic controllers possess good robustness qualities.