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。
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.
作者
陈晓
王晓燕
王新民
刘雪超
CHEN Xiao;WANG Xiaoyan;WANG Xinmin;LIU Xuechao(College of Mechanical and Electrical Engineering, Xi’an University of Architecture and Technology, Xi’an 710000, China;College of Automation, Northwestern Polytechnical University, Xi’an 710129, China)
出处
《计算机工程与应用》
CSCD
北大核心
2019年第21期254-260,270,共8页
Computer Engineering and Applications
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
tiltrotor aircraft
flight control system
smooth conversion
hybrid particle swarm
neural network
