Nonlinear Modeling of Small Unmanned Helicopters Based on Double Neural Networks

Abstract

This paper proposes a double neural network modeling method by studying the modeling problem for small unmanned helicopters. Based on the traditional neural network modeling method, the error compensation model is introduced, and the height control identification model of small unmanned helicopter based on BP network is established. Finally, the effectiveness and feasibility of the proposed method are verified by simulation experiments compared with traditional modeling methods. The simulation results show that the method of double neural network modeling greatly improves the approximation accuracy and generalization ability of the model.