LAUSR

Abstract A novel model-free Adaptive Wavenet PID (AWPID)-based controller for enabling an Unmanned Aircraft System (UAS) to transport a cable suspended load of unknown characteristics is presented. The control design enables the UAS to perform a trajectory tracking task, based solely on the knowledge of the UAS position. The methodology is based on a novel framework, which identifies inverse error dynamics using a Wavelet Neural Network (WNN) with daughter Mexican hat wavelets activation functions. A real-time load transportation task consisting of a multi-rotorcraft UAS carrying a cable suspended load of unknown characteristics validates the effectiveness of the trajectory tracking control strategy, showing smooth control signals even when the dynamic model of the UAS and the load characteristics are not known.