Deep Learning Methods for System Identification of UAV

Abstract

Nowadays, deep learning is the most prominent subject in the machine learning field. With the bloom of researchers in this field, numerous novel algorithms are used to solve everyday life problems. The control systems field is one of the subjects that get many impacts of machine learning emergence. System identification of Unmanned Aerial Vehicles (UAV) is one of the control systems problems that could be solved by using deep learning methods. In this paper, Recurrent Neural Networks (RNNs) are applied to identify the system of UAV. Three different models of Deep RNNs have been tried, and the results implied that the RNNs-1 was giving more excellent performance both on the testing MSE and RMSE with the values equal to 0.0006 and 0.0242, successively.