Aerial platform vehicle is a kind of construction vehicle which can hoist personnel to the appointed location in the aerial for installation or maintenance. There are several types of aerial platform vehicle, including telescopic-boom, folding-boom and mixing-boom styles. As the widely use of the light-long-arms in the structure of arms, elastic deformations of them are not be neglected. The dynamics equations of the arm system are established based on flexible multi-body dynamics theory and Lagrange’s equation in this paper. Based on the dynamics equations, the trajectory tracking control of work platform of aerial platform vehicle is carried on. Simulation results show that the model created is plausible. Furthermore, in order to realize accurate positioning and suppress vibration of work platform, the relevant research work is carried out. In this dissertation, the flexible multi-body dynamics equations of the arm system of folding-boom aerial platform vehicle are established and the control problems of trajectory tracking are studied based on the flexible multi-body dynamics theory, which was with the support of Jiangsu Special Fund of Scientific and Technological Achievements Transformations “The Research and Industrialization of Robotic Aerial Platform Vehicle of Intelligent Control Series”. The research work in this paper will have important significant for the improving of the control level of aerial platform vehicle. The main work and the obtained results in this paper are as follows: Firstly, the development of aerial platform vehicle and the technology status at home and abroad are given. The modeling and control method of the flexible multi-body dynamics system are introduced. Considering the elastic deformations of arms, the dynamics equations of the arm system of folding-boom aerial platform vehicle are established based on the flexible multi-body dynamics theory and Lagrange’s equation. Secondly, a backstepping controller use for the trajectory tracking control and vibration suppressing of work platform is presented. Simulation results show that the proposed controller is very effective for control objective. Thirdly, a neural network backstepping controller is presented by using neural network to approximate unknown parts of the model. Simulation results show that this controller can realize the trajectory tracking control and vibration suppressing of work platform when the accurate model is unknown. Forthly, adapt...
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