Output constrained neural adaptive control for a class of KKVs with non-affine inputs and unmodeled dynamics

X. Ning, J. Liu, Z. Wang, C. Luo

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

In this paper, an adaptive neural output-constrained control algorithm is proposed for a class of non-affine kinetic kill vehicle (KKV) systems. The key point is that the non-affine control law can be designed and the output of the KKV system conform to the output limit with the aid of the proposed method. Due to the aerodynamic moments, the actual control torque is non-affine, which can be addressed by introducing an integral process to the design of the controller. Besides, in order to improve the control precision, a nonlinear mapping is put forward so that the output constraint can be transformed to the constraint of the introduced dynamic signal that can be simply achieved. From the simulation results it can be concluded that the states of the KKV system can track the desired trajectories in spite of different working conditions and the control precision is higher compared with other control methods.

源语言英语
页(从-至)134-151
页数18
期刊Aeronautical Journal
128
1319
DOI
出版状态已出版 - 1 1月 2024

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