DocumentCode :
2772145
Title :
Attitude and Vibration Control of Flexible Spacecraft Using Adaptive Inverse Disturbance Canceling
Author :
Yaqiu Liu
Author_Institution :
Northeast Forestry Univ., Harbin
fYear :
0
fDate :
0-0 0
Firstpage :
2478
Lastpage :
2484
Abstract :
An adaptive inverse disturbance canceling method for normal pointing attitude control and vibration reduction of an orbiting spacecraft with flexible appendage is proposed by defining the correlative vibration as "modal vibration disturbance". In this method, the dynamical system of the rigid spacecraft is first modeled using NARX neural network. Then, a very close copy of the rigid model, disturbance-free match to plant, is fed the same input as the plant. The difference between the disturbed output of the plant and the disturbance-free output of the copy model is the estimation of modal vibration disturbance, which is the input to the disturbance canceling filter. Upon that, the output of filter is subtracted from the plant input to effect cancellation of the plant disturbance, such that the incentive element of modal vibration is cancelled in principle and the vibration can be effective reduced. In addition, considering the variations and uncertainty of the plant, the plant model and canceller filter are adaptive in real-time. Finally, the analysis, design and simulation for the problem have been carried out systemically. Simulation results demonstrate that all above problems are solved by the research productions in this dissertation.
Keywords :
attitude control; neurocontrollers; space vehicles; vibration control; NARX neural network; adaptive inverse disturbance canceling; attitude control; dynamical system; flexible appendage; flexible spacecraft; modal vibration disturbance; orbiting spacecraft; vibration control; vibration reduction; Adaptive control; Adaptive filters; Analytical models; Attitude control; Neural networks; Production; Programmable control; Space vehicles; Uncertainty; Vibration control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.247097
Filename :
1716427
Link To Document :
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