Entropy Fuzzy System Identification for the Dynamics of the Dragonfly-like Flapping Wing Aircraft

Abstract

In this work we present non-linear system identification for a class of the dragonfly-like flapping wing aircraft. We model the system in its vertical and all attitude loops (roll, pitch, and yaw) as well as its actuator dynamics. Based on a set of input-output data, obtained from first principle modelling; we perform the entropy fuzzy system identification to derive the open loop dynamics of the aircraft using the Mamdani Fuzzy inference method, which is more intuitive, despite being non-linear. This will make the proposed models well-suited to non-expert users (e.g. average drone operators). Our research indicates that the information entropy is very effective to maximize the system accuracy while avoiding overfitting problems. Through numerical simulation, we demonstrate the efficacy of the proposed fuzzy models as we can achieve reasonably good average modelling accuracy of around 90 % for all attitude loops.