Synthesis of optimal feedback guidance law for homing missiles using neural networks
✍ Scribed by N. Rahbar; M. Bahrami
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 81 KB
- Volume
- 21
- Category
- Article
- ISSN
- 0143-2087
No coin nor oath required. For personal study only.
✦ Synopsis
Most existing missiles are guided by proportional navigation guidance (PNG) law, but PNG is a particular case for LQ guidance rule with two main assumptions of small line-of-sight angles and negligible acceleration along the line-of-sight. However, most missile engagements exceed these limits because of high tangential and normal accelerations. Unfortunately, it is not possible to determine the feedback guidance law for non-linear systems such as homing missiles in real-time. We use arti"cial neural networks to synthesize feedback laws for homing missiles with non-linear state equations. We "rst obtain an open-loop optimal numerical solution for non-linear state equations and then use these data to train a feed-forward multilayer neural network in an o!-line session. The network is then used e!ectively in a real-time for feedback guidance method. Simulation results show that this neural networks guidance method can e$ciently produce an optimal feedback law in spite of relatively simple network architecture.