Application of iterative learning tuning to a dragonfly-like flapping wing micro aerial vehicle

The flight control design of a dragonfly-like flapping wing micro aerial vehicle (FWMAV) is studied in this paper. The main contribution of this work is to design an appropriate flight controller by incorporating a linear-quadratic regulator (LQR) method and an iterative learning tuning (ILT). The linear model of dragonfly-like FWMAV is developed at the equilibrium point. Then a linear-quadratic regulator approach is applied to design the flight controller of FWMAV. However the flight controller performance of FWMAV is sensitive to the input weighting matrix of LQR. In order to improve the flight controller, an iterative learning tuning is developed to optimize the input weighting matrix of LQR problem due to unknown constraints and relations between the state and the control input. Numerical simulation results show that the effectiveness and convergence performance of the flight controller of FWMAV are obtained.