摘要
该文采用一种基于鸟类生物学模型的复合前馈控制与突变控制相结合的改进算法控制策略,应用光电设备捕捉飞鸟,强声和激光进行跟随驱离,实现机场智能驱鸟功能。在设备云台伺服电机跟随伺服性能的基础上,对鸟类在飞行过程中的突变状况进行研究。首先针对鸟类在系统中的飞行状况和设备干扰状况建立鸟类实时状态模型,并根据此模型建立模糊控制规则库,然后通过突变分析,设计出基于鸟类生物学模型的非线性控制器,接着结合设备干扰定性拟合鸟类在干扰下的突变分析,最后建立复合前馈控制系统并加入突变预测的非线性控制器。对比了传统跟随驱动方式和复合前馈突变方式,系统响应速度更快、稳定性更高,并通过实验验证了策略的效果。
In this paper,an improved algorithm control strategy based on the combination of compound feedforward control and mutation control based on bird biological model is applied to photoelectric equipment to catch birds,and strong sound and laser are used to drive them away,so as to realize the intelligent bird drive function at the airport.Based on the following servo performance of the servo motor of the equipment pan-tilt,the sudden change of bird targets during flight is studied.Firstly,the real-time state model of birds is established according to the flight status and equipment interference of bird targets in the system,and the fuzzy control rule base is established according to this model.Then,a nonlinear controller based on bird biological model is designed through catastrophe analysis,and then the catastrophe analysis of bird targets under interference is qualitatively fitted by combining equipment interference.Finally,a composite feedforward control system is established and a nonlinear controller for catastrophe prediction is added.Compared with the traditional follow-up drive mode and the compound feedforward mutation mode,the system has faster response speed and higher stability,and the effect of the strategy is verified by experiments.
作者
孙磊
王晨
柳士伟
肖鑫
SUN Lei;WANG Chen;LIU Shiwei;XIAO Xin(School of Electrical Engineering,Yancheng Institute of Technology,Yancheng 224000,China;Support Team Directly Under the Air Force Support Department of the Eastern Theater,Nanjing 210000,China)
出处
《自动化与仪表》
2024年第1期155-159,共5页
Automation & Instrumentation
关键词
前馈控制
突变控制
鸟类模糊规则库
鸟类模型搭建
feedforward control
catastrophe control
bird fuzzy rule base
bird model building