计算机与现代化

• 人工智能 •    下一篇

基于模糊神经网络PID的舵机控制系统

  

  1. (南京理工大学航空宇航系,江苏南京210094)
  • 收稿日期:2017-08-14 出版日期:2018-04-03 发布日期:2018-04-03
  • 作者简介:卜庆伟(1991-),男,辽宁阜新人,南京理工大学航空宇航系硕士研究生,研究方向:航空控制算法; 陈雄(1977-),男,四川绵阳人,教授,博士生导师,博士,研究方向:航空及宇航控制; 柴金宝(1993-),男,黑龙江哈尔滨人,硕士研究生,研究方向:航空控制工程; 崔二伟(1993-),男,山西临汾人,硕士研究生,研究方向:测量与控制。
  • 基金资助:
    国家自然科学基金资助项目(51606098); 江苏省自然科学基金资助项目(BK20140772)

A Servo Control System Based on Fuzzy Neural Network PID

  1. (Department of Aeronautics and Astronautics, Nanjing University of Science and Technology, Nanjing 210094, China)
  • Received:2017-08-14 Online:2018-04-03 Published:2018-04-03

摘要: 针对某型号导弹中舵机控制系统进行优化研究。对于具有非线性、时变特性的复杂系统,在分析传统PID控制算法和模糊神经网络控制算法的基础上,提出一种经过改进的模糊神经网络PID控制器。通过采用自组织学习阶段和有教师学习阶段的分阶段学习方式,提高网络的学习效率。建立直流无刷舵机控制系统的数学模型,利用MATLAB进行仿真分析。实验结果表明,所设计的控制器对阶跃响应更加迅速,基本无超调,对舵偏角指令执行准确,相位移动更小。

关键词: 模糊神经网络, 直流无刷舵机, PID控制器, MATLAB仿真

Abstract: This paper aims at optimizing the control system of servo in a certain missile. For a complex system with nonlinear and time-varying characteristics, an improved fuzzy neural network PID controller is proposed on the basis of the analysis of traditional PID control algorithm and fuzzy neural network control algorithm. Phased learning mode improves the network learning efficiency by the way of adopting self-organization learning and learning with a teacher. The mathematic model of DC brushless servo control system is established. Meanwhile, the simulation analysis is carried out by MATLAB as well. The experimental results show that the designed controller has faster step response with no overshoot basically and performs accurately with smaller phase shift under the rudder skew command.

Key words: fuzzy neural network, DC brushless servo, PID controller, MATLAB simulation

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