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| Received:May 02, 2012Revised:December 10, 2012 |
| 基金项目:This work was supported by the Science and Engineering Research Council (SERC) Research Grant (No. 092 101 00558). |
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| Ballistic learning control: formulation, analysis and convergence |
| Jianxin XU,Deqing HUANG,Wei WANG |
| (Department of Electrical and Computer Engineering, Faculty of Engineering, National University of Singapore) |
| Abstract: |
| In this paper, we formulate and explore the characteristics of iterative learning in ballistic control problems. The iterative learning control (ILC) theory provides a suitable framework for derivations and analysis of ballistic control under learning process. To overcome the obstacles caused by uncertain gradient and redundant control input, we incorporate extra trials into iterative learning. With the help of trial results, proper control and updating direction can be determined. Then, iterative learning can be applied to ballistic control problem. Several initial state learning algorithms are studied for initial speed control, force control, as well as combined speed and angle control. In the end, shooting angle learning in the basketball shot process is simulated to verify the effectiveness of iterative learning methods in ballistic control problems. |
| Key words: Ballistic control Iterative learning control Initial state learning Convergence |
