An Online Reinforcement Learning Wing-Tracking Mechanism for Flexible Wing Aircraft

摘要

Flexible wing aircraft are gaining an increasing interest due to their salient features, such as inexpensive market price, low-cost operation, in-flight robustness, multi-purpose use, and their ability to operate with very little infrastructure. The continuous variations in the aerodynamics of the wing and additionally the kinematic and dynamic constraints that evolve due to the wing-fuselage interactions make the modeling task of such systems ultimately challenging. An online model-free adaptive control mechanism based on two linear actuation systems is proposed in this manuscript to fulfill different pitch-roll maneuvers. The mechanism employs model-free tracking control strategies and utilizes a real-time value iteration-based reinforcement learning process. The adaptation of the control gains is accomplished online using means of adaptive critics.