Adaptive neural network control of an aerial work platform's arm

An aerial work platform (AWP) is a type of off highway vehicle with a long beam to provide temporary access to inaccessible areas [1]. The motivation of the research is to increase its productivity, safety and reduce the manipulation complexity during the operation process. In this paper, a simplified two-link model of AWP's arm is given. The control scheme based on neural network modeling technology is employed to steer the AWP's arm to track the desired trajectories asymptotically, which requires neither the evaluation of inverse dynamical model nor the time-consuming training process. The simulation results validate the effectiveness of the proposed approach.