Azin Yazdekhasti - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Esfahan, Iran
Khoshnam Shojaei - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Esfahan, Iran

This paper aims to propose an efficient control algorithm for the unmanned aerial vehicle (UAV) helicopter with underactuated dynamics. An intelligent control system isproposed by using radial basis function neural network (RBFNN). Moreover, based on sliding-mode approach, theadaptive tuning laws of RBFNN can be derived. Then, thedeveloped RBFNN control system is applied to an UAV helicopter for achieving desired trajectory tracking. From the simulationresults, the control scheme has been shown to achieve favorable control performance for the UAV helicopter with underactuateddynamics even it is subjected to parameter uncertainties and external disturbance

Unmanned aerial vehicle helicopter, Radial basis function neural network, Sliding mode control, Adaptive robust