兵工自动化2025，Vol.44Issue(4)：1-5,25,6.DOI:10.7690/bgzdh.2025.04.001
基于RBFSMC车载武器行进间稳定控制
Moving Stability Control of Vehicular Weapon Based on RBFSMC
李佳帅 1高强 1邓桐彬 2李勃 1季强 1符伟鹏1
作者信息
- 1. 南京理工大学机械工程学院,南京 210094
- 2. 中国电子科技集团公司第二十八研究所陆上作战指挥信息系统研究部,南京 210000
- 折叠
摘要
Abstract
A sliding mode control strategy based on RBF neural network was designed in order to solve the problem that the on-road firing of a vehicle-mounted machine gun would be affected by a series of nonlinear factors.Based on the strong robustness of sliding mode control,a real-time disturbance observer is used to accurately observe the disturbance,and the unique advantage of RBF neural network in nonlinear function approximation is used to approximate the uncertainties of the system,and an adaptive law is designed to ensure the asymptotic stability of the system.The switching gain is dynamically adjusted by RBF neural network to further suppress the chattering problem and the influence of nonlinear factors such as parameter change and external disturbance.The simulation results show that compared with the conventional sliding mode control,the proposed control strategy can effectively improve the stability control precision of the vehicle-mounted gun system.关键词
RBF神经网络/稳定控制/滑模控制/车载武器/扰动观测器Key words
RBF neural network/stability control/sliding mode control/vehicle-mounted weapon/disturbance observer分类
武器工业引用本文复制引用
李佳帅,高强,邓桐彬,李勃,季强,符伟鹏..基于RBFSMC车载武器行进间稳定控制[J].兵工自动化,2025,44(4):1-5,25,6.
