Nonlinear and neural network-based control of a small four-rotor aerial robot

Abstract

Small four-rotor aerial robots, so called quadrotor UAVs, have an enormous potential for all kind of near-area surveillance and exploration in military and commercial applications. In addition, they offer the possibility to fly either in-or outdoor. However, stabilizing control and guidance of these vehicles is a difficult task because of the nonlinear dynamic behavior. This paper describes the development of a nonlinear vehicle control system based on a combination of state-dependent Riccati equations (SDRE) and neural networks. Some first simulation results underline the performance of this new control approach for the current realization.