Adaptive attitude and position control of an insect-like flapping wing air vehicle

This study describes an adaptive sliding mode technique for attitude and position control of a rigid body insect-like flapping wing model in the presence of uncertainties. For this purpose, a six-degrees-of-freedom nonlinear and time-varying dynamic model of a typical hummingbird is considered for simulation studies. Based on the quasi-steady assumptions, three major aerodynamic loads including delayed stall, rotational lift and added mass are presented and analyzed, respectively. Using the averaging theory, a time-varying system is then transformed into the time-invariant system to design the adaptive controller. The controller is designed so that the closed-loop system will follow any desired trajectory without prior information about uncertainties. In the final stage, in order to find the wing kinematic parameters and to ensure the feasibility of the control commands, two feedforward artificial neural networks are developed and trained using aerodynamic forces and moments from the open-loop simulation data. In comparison with non-adaptive technique, it is shown that the adaptive sliding mode controller is able to stabilize the vehicle in the presence of input disturbances and model uncertainties.