Neural dynamics for adaptive attitude tracking control of a flapping wing micro aerial vehicle

Abstract

This paper proposes a class of neural dynamics models based on a neural dynamic approach to realize attitude tracking control of a flapping wing micro aerial vehicle (FWMAV), different from the existing conventional controllers. Firstly, from the perspective of FWMAV attitude tracking control, an attitude tracking model is presented. Further theoretical analyses reveal that there exist theoretical errors on such a controller when solving the attitude tracking control problem. To remedy its deficiency, we propose a class of adaptive neural dynamics models with activation functions. Different from the existing controller, the adaptive neural dynamics model adopts different activation functions to accelerate the convergence speed of attitude tracking errors and makes errors converge to zero in a short time. Finally, simulation results and theoretical analyses are provided, which verify that the proposed controllers possess the superiority and effectiveness.