系统仿真学报 ›› 2017, Vol. 29 ›› Issue (2): 409-417.doi: 10.16182/j.issn1004731x.joss.201702024

• 仿真应用工程 • 上一篇    下一篇

飞机舵机电液加载系统多余力抑制方法研究

刘晓琳, 王春婷   

  1. 中国民航大学,天津 300300
  • 收稿日期:2015-05-05 修回日期:2015-08-10 出版日期:2017-02-08 发布日期:2020-06-01
  • 作者简介:刘晓琳(1978-),女,黑龙江哈尔滨,博士,副教授,研究方向为智能控制、故障诊断;王春婷(1990-),女,山东德州,硕士生,研究方向为智能控制、故障诊断。
  • 基金资助:
    国家自然科学基金(U1333111),中央高校基金(3122015C013)

Research of Strategy to Restrain Surplus Force of Aircraft Rudder Electro-Hydraulic Loading System

Liu Xiaolin, Wang Chunting   

  1. College of Aeronautical Automation of Civil Aviation University of China, Tianjin 300300, China
  • Received:2015-05-05 Revised:2015-08-10 Online:2017-02-08 Published:2020-06-01

摘要: 针对飞机舵机电液加载系统存在的多余力干扰不易抑制的问题,提出了结合橡胶-金属缓冲弹簧、飞机舵机位移指令前馈、基于动态RBF神经网络在线辨识的单神经元PID输出负载力反馈的复合控制器结构功能及控制策略利用蚁群聚类算法优化的动态RBF神经网络对系统进行在线辨识,获得Jacobian信息,由单神经元PID控制器完成控制参数的在线自整定。仿真结果表明,该方法可以在实验室条件下对于模拟飞机舵机所受到的力载荷实现快速、准确的加载,能保证系统的稳定性且具有较强的鲁棒性。

关键词: 飞机舵机电液加载系统, 多余力, 单神经元PID控制器, 动态RBF神经网络, 蚁群聚类算法

Abstract: For the problem that is caused by surplus torque of aircraft rudder electro-hydraulic loading system is not easy to inhibit, compound controller structure function and control strategy were proposed that combined rubber-metal buffer spring, the displacement of steering gear and speed feed forward of aircraft rudder and the output force feedback use single neuron PID based on dynamic RBF neural network on-line identification. Ant clustering algorithm was used to optimize the dynamic RBF neural network to identify the object online to obtain Jacobian information, then use the single neuron PID controller complete control parameters online self-tuning control. The simulation results show that this method can achieve rapid and accurate load for simulated aircraft rudder power load under laboratory conditions, and can guarantee the stability of the system and has strong robustness.

Key words: aircraft rudder electro-hydraulic loading system, surplus torque, single neuron PID controller, dynamic RBF neural network, ant clustering algorithm

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