Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (21): 254-260.DOI: 10.3778/j.issn.1002-8331.1806-0403

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Improved Design of Smooth Transition Control System for Tiltrotor Aircraft

CHEN Xiao, WANG Xiaoyan, WANG Xinmin, LIU Xuechao   

  1. 1.College of Mechanical and Electrical Engineering, Xi’an University of Architecture and Technology, Xi’an 710000, China
    2.College of Automation, Northwestern Polytechnical University, Xi’an 710129, China
  • Online:2019-11-01 Published:2019-10-30

改进的倾转旋翼机平稳过渡控制系统设计

陈晓,王晓燕,王新民,刘雪超   

  1. 1.西安建筑科技大学 机电工程学院,西安 710000
    2.西北工业大学 自动化学院,西安 710129

Abstract: Aiming at the problem that the transition process of tiltrotor aircraft is extremely unstable in conversion mode and the control system is difficult to design, the scheme of smooth transition control system for tiltrotor aircraft is studied. The structure of the smooth transition control system is designed, and the improved neural network PID control law based on hybrid particle swarm optimization is proposed, and then the specific flow of the control algorithm is given. Simulation validation is carried out based on XV-15 tilt-rotor aircraft model. The results show that the proposed method is smoother than the curve obtained by the BP neural network PID method, there is no large amplitude oscillation, and the expected control effect is achieved.

Key words: tiltrotor aircraft, flight control system, smooth conversion, hybrid particle swarm, neural network

摘要: 针对倾转旋翼机在过渡模式下的过渡过程极其不稳定,控制系统设计难度大的问题,研究了倾转旋翼机平稳过渡控制方案。设计了平稳过渡控制系统结构,提出了改进的基于杂交粒子群的神经网络PID控制律设计,给出了该控制算法的具体流程。以XV-15为例进行仿真验证,结果表明提出的方法比BP神经网络PID方法得到的曲线变化更加平稳,没有出现幅值较大的震荡,达到了预期控制效果。

关键词: 倾转旋翼机, 飞行控制系统, 平稳过渡, 杂交粒子群, 神经网络