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作 者:张宸睿 张鹏飞[1] 赵永娟[1] 程文铮 米江勇 ZHANG Chenrui;ZHANG Pengfei;ZHAO Yongjuan;CHENG Wenzheng;MI Jiangyong(Intelligent Weapon Research Institute,North University of China,Taiyuan 030051,China)
出 处:《火力与指挥控制》2024年第8期60-67,79,共9页Fire Control & Command Control
摘 要:为提升自行高炮随动系统的抗干扰能力以及自行高炮行进间射击精度,采用了一种基于单神经元自适应PID的控制方法,利用神经元的自学习及自校正能力对控制效果进行改善,以提升随动系统的扰动补偿能力。仿真结果表明:当高炮在B级、D级以及F级路面下行驶时,采用该方法的随动系统输出曲线的波动范围分别减小了0.14%、0.65%和4.72%,在突加扰动的情况下,再次跟踪到目标信号的时间分别缩短了0.04 s、0.03 s和0.02 s,根据实验数据可知在单神经元自适应PID控制器的作用下,当系统受到干扰后能够更快地跟踪到目标信号,且稳态精度更高。In order to improve the anti-disturbance ability and firing accuracy of the self-propelled anti-aircraft gun servo system,a control method based on single neuron adaptive PID is adopted in this paper.The self-learning and self-correcting abilities of neurons are used to improve the control effects,so as to improve the disturbance compensation ability of the servo system.The simulation results show that:the fluctuation range of the output curve of the servo system by this method is reduced by 0.14%,0.65%and 4.72%respectively when the anti-aircraft gun is driving under the class B,class D and class F road surface.Under the condition of sudden disturbance,the time to track the target signal again is shortened by 0.04 s,0.03 s and 0.02 s respectively.According to the experimental data,under the action of single neuron PID controller,when the system is disturbed,it can track the target signal faster,and the steady-state accuracy is higher.
分 类 号:TJ35[兵器科学与技术—火炮、自动武器与弹药工程]
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