Adaptive flight control law based on neural networks and dynamic inversion for micro-aerial vehicles

Abstract

The paper presents two new adaptive systems, for the attitude׳s control of the micro-aerial vehicles (MAV׳s) – insect type. The dynamic model describing the motion of MAV׳s with respect to the Earth tied frame is nonlinear and the design of the new adaptive control system is based on the dynamic inversion technique. The inversion error is calculated with respect to the control law and two matrices (inertia and dynamic damping matrices) which express the deviation of the estimated matrices relative to the calculated ones (the matrices from the nonlinear dynamics of MAV׳s) in conditions of absolute stability in closed loop system by using the Lyapunov theory. To completely compensate this error, an adaptive component (output of a neural network) is added in the control law. The system also includes a second order reference model which provides the desired attitude vector and its derivative. The two variants of the new adaptive control system are validated by complex numerical simulations.