The control and guidance of autonomous vehicles has become a common topic of research amongst control theory mathematicians and engineers. There exist several control strategies, which can handle nonlinearities in the system, for controlling unmanned vehicles. In this paper a neural network based control strategy implemented on a 3DOF tandem helicopter model is discussed. This controller can handle systems with non-linear dynamicswith necessary changes in the neural network parameters. The focus of this paper is to perform system identification by learning the inverse model of the system. While most such algorithms use an artificial neural network,a wavelet neural network has been improvised upon in this work. © Research India Publications.