Fuzzy Logic Model-less 3-DOF Flight Controllers

The design of a robust flight control system without prior knowledge of the mathematical/aerodynamic model of a specific aircraft is a challenge undertaken by the Robust Learning Control program at NASA Langley Research Center. This paper proposes and numerically implements a Type-l fuzzy logic controller design for aircraft control in 3-DOF (Pitch, Roll and Yaw). The fuzzy controller is created upon a rule base of generic flight control maneuvers. The goal for the model-less controller is to enable real time aerodynamic modeling to take place to enable the design of a model-based controller. Thus, the model-less controller needs to provide acceptable performance without manual tuning. The implemented control architecture for each degree-of-freedom can use up to two channels, providing an absolute and incremental controller command as necessary. The absolute channel is designed to reject disturbances and decrease rise time, while the incremental channel provides tracking and reduced steady state error. The pitch motion is controlled by two channels and the roll motion is controlled only using an absolute channel. For the yaw motion the two possible options (Absolute + Incremental and Absolute) were implemented and compared. Additionally, a PID controller has been designed and implemented for the thrust of the aircraft to sustain aircraft altitude and total velocity when commanding different attitudes. The pitch and roll controllers have been tested in the 12-foot low speed wind tunnel at the NASA Langley Research Center. All of the controllers have been tested with an F-16 low-fidelity aircraft simulator. Several command angles of the 3-DOF for the aircraft have been used to test the controllers. After analysis on the controller's performance, a new systematic design of the fuzzy rule base for a generic flight control has been proposed and tested. The proposed controllers were implemented on a high-fidelity F-16 aircraft and at different initial conditions to investigate the effectiveness of the controllers when the aerodynamic model has been changed. Overall, the fuzzy logic controllers for pitch, roll and yaw show successful performance with quick response and low steady state error.