Supervisor:
Southwest Ordnance Industry Bureau
Organizer:
Chongqing Ordnance Industry Society
Chongqing University of Technology
Chongqing University of Technology
Research on RBF neural network guidance law for overload control
| DOI: | 10.11809/bqzbgcxb2023.10.020 |
| Keywords: | Neural network; terminal guidance; proportional guidance law; overload control |
| Abstract: | Aiming at the interception problem of targets with high maneuverability and high penetration ability, through the analysis of the relationship between overload and proportional coefficient and line of sight angular rate in the guidance process of the guidance law, a three dimensional missile target relative motion model based on the line of sight coordinate system is established, and the acceleration representation of proportional guidance law in this coordinate system is studied, and the RBF neural network model to realize K value adaptive adjustment is designed accordingly. Compared with the normal overload and attack time of pure proportional guidance law, the effectiveness of RBF neural network guidance law in suppressing line of sight angular rate chattering and overload control is verified on the premise of reducing guidance performance. |
| Issue: | Vol. 44 No. 10 (2023) |
| Published: | 2023-10-28 |
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