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Research On Modeling And Dynamic Simulation Of Unmanned Aerospace Vehicle

Posted on:2007-04-10Degree:MasterType:Thesis
Country:ChinaCandidate:X K ZhaoFull Text:PDF
GTID:2178360185959539Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
Combined with the important research plan—several great basic problems on aerospace vehicle that is granted by National Natural Science Foundation of China (NSFC), this paper is mainly focusing on the theoretic research in the process of ascent.Because of aerospace vehicle's military and civil function in recent years, it has been becoming more and more important. So the 6-DOF model is established on the basis of the information that is openly published at home and abroad in order to match the basic research and our national demands.In this paper, dynamic inversion control law is designed to eliminate its global non-linearization and unstable aerodynamic force etc. And based on the time-scale separation principle, the control system can be divided into fast loop and slow loop. But there are still lots of unknown disturbances that may cause great damages to stability when flying. So the disturbance observer and adaptive control based on neural network are devoted to solve this problem.The principle of disturbance observer is to take all unknown disturbances like modeling error as systematic disturbance to approach, then use the output to compensate the systematic inversion error. And the idea of on-line compensation with neural network is introduced to eliminate the inversion error which is caused by the inaccurate modeling through the adaptive adjustment of weight values.Both of these ideas can eliminate the bad influence caused by inversion error effectively, reduce the need of accurate modeling in control design greatly, and increase the robustness of control system.At last this paper introduces the technology of plane modeling by 3DS MAX, the method of using OpenGL engine, and establishing the terrain under the algorithm of Diamond-Square.
Keywords/Search Tags:Unmanned aerospace vehicle, Dynamic inversion, Disturbance observer, Neural network, Adaptive control, Robust control, Animation simulation
PDF Full Text Request
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