基于改进单神经元PID控制的航检设备稳定性研究  

Research on Stability of Aviation Inspection Equipment Based on Improved Single Neuron PID Control

作　　者：张裕栋 ZHANG Yudong(Aeronautical Engineering Institute,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学航空工程学院,天津300300

出　　处：《控制工程》2025年第3期394-399,共6页Control Engineering of China

基　　金：国家高技术研究发展计划项目(2014AA110501)。

摘　　要：随着航空器维修自动化的高速发展,移动端航检设备已逐渐应用于航空器的日常巡检,但移动端设备作业过程中产生的振动会降低信息采集精度甚至损害航空器。针对负载末端机械谐振的抑制问题,提出了一种基于粒子群优化(particle swarm optimization, PSO)算法改进的单神经元PID控制策略,在实现单神经元PID自适应调节的基础上,采用PSO算法对单神经元PID控制中的赫布(Hebb)学习速率进行参数整定。结果表明,所提出的控制方法相较于标准PID控制和神经元PID控制具有更好的振动控制时效和控制精度,并且验证了该方法在航空器巡检设备维修过程中的稳定性和有效性。With the rapid development of aviation maintenance automation,mobile terminal aerial inspection equipment is gradually applied to the daily inspection of aircraft.However,the vibration generated during the operation of the mobile terminal equipment will reduce the accuracy of information collection and even damage the aircraft.For the problem of mechanical resonance suppression at the end of the load,a control strategy based on PSO control improved single neuron PID control is proposed.Based on realizing the adaptive adjustment of single neuron PID control,the PSO control iterative optimization algorithm is used to tune the parameters of Hebb learning rate in single neuron PID control.The results show that the proposed control method has better vibration control timeliness and control accuracy than standard PID control and neuron PID control,and verifies its stability and effectiveness in the maintenance process of aircraft inspection equipment.

关 键 词：航空维修 自适应控制 粒子群优化 抖动抑制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]