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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yaqiu Liu |
| Copyright Year | 2006 |
| Description | Author affiliation: Northeast Forestry Univ., Harbin (Yaqiu Liu) |
| 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. |
| Starting Page | 2478 |
| Ending Page | 2484 |
| File Size | 329573 |
| Page Count | 7 |
| File Format | |
| ISBN | 0780394909 |
| DOI | 10.1109/IJCNN.2006.247097 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-07-16 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Attitude control Vibration control Space vehicles Programmable control Adaptive control Neural networks Uncertainty Adaptive filters Analytical models Production |
| Content Type | Text |
| Resource Type | Article |
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