Three-dimensional Adaptive Neural Network Guidance Law against Maneuvering Targets

Authors

Yujie Si, Beijing Institute of Electronic System Engineering, Beijing 100854, China;
Xiong Hua, Beijing Institute of Electronic System Engineering, Beijing 100854, China;
Zhe Li, Beijing Institute of Electronic System Engineering, Beijing 100854, China;

Abstract

Abstract: The problem of designing a three-dimensional nonlinear guidance law accounting for saturation nonlinearity is concentrated to attack maneuvering targets. To solve the physical constraints of missile actuators, an anti-disturbance and anti-saturation terminal sliding mode guidance law is provided based on radial basis functions neural networks and adaptive method. The guidance law is bounded and ensures that the system state is uniformly ultimately bounded. Compared with the traditional anti-saturation guidance law, it has the advantages of fast convergence speed and high precision. Numerical simulations are introduced to demonstrate the effectiveness and superiority of the designed composite guidance law in theory.

Recommended Citation

Si, Yujie; Hua, Xiong; and Li, Zhe (2021) "Three-dimensional Adaptive Neural Network Guidance Law against Maneuvering Targets," Journal of System Simulation: Vol. 33: Iss. 2, Article 23.
DOI: 10.16182/j.issn1004731x.joss.19-0434
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss2/23

First Page

453

Revised Date

2020-05-17

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-0434

Last Page

460

CLC

TP391.9

Recommended Citation

Si Yujie, Xiong Hua, Li Zhe. Three-dimensional Adaptive Neural Network Guidance Law against Maneuvering Targets[J]. Journal of System Simulation, 2021, 33(2): 453-460.

Corresponding Author

Xiong Hua,

DOI

10.16182/j.issn1004731x.joss.19-0434