摘要
为了研究飞机防滑刹车系统,在分析滑移率控制式飞机防滑刹车系统的工作原理基础上,将基于RBF神经网络算法的PID控制方法引入飞机防滑刹车系统中,实现最佳滑移率式的飞机防滑刹车控制。以某型飞机为例,针对不同的跑道(干、湿、冰)情况,将该方法和传统的PID控制方法在MATLAB环境下进行了数字仿真,仿真结果表明:基于RBF神经网络PID的控制方法较传统的PID控制方法,有更好的刹车控制效果,并具有较强的鲁棒性;采用基于滑移率式的RBF神经网络PID控制可以大大地提高飞机防滑刹车效率,为飞机防滑刹车系统的控制提供一条新的思路。
By analyzing the principle of aircraft anti-skid braking system,an optimal control method of aircraft anti-skid braking system based on wheel slip-ratio is presented,and the PID control based on RBF neural network is used to realize the optimization of aircraft anti-skid braking system control performance.Take a type of aircraft for example,with different runway condition（dry/wet/ice）,the computer numeral simulation with MATLAB is established.Compared the control performance of traditional PID control with PID control based on RBF neural network,the result show that PID control with RBF neural network method can achieve a more ideal control effect and has a stronger robust characteristic than traditional PID control,and the braking efficiency has been improved greatly by controlling wheel slid-ration,it has provided a new way for controlling aircraft anti-skid braking system.
出处
《计算机仿真》
CSCD
北大核心
2010年第10期24-28,共5页
Computer Simulation
关键词
飞机防滑刹车
滑移率
神经网络
控制
仿真
Aircraft anti-skid braking
Slid-ratio
Neural network
Control
Simulation
作者简介
刘泽华（1981-），男（汉族），湖北监利人，硕士，工程师，研究方向：飞机起落架液压系统控制。
高亚奎（1959-），男（汉族），陕西大荔人，博士，研究员，副总设计师，研究方向为飞机机电系统、飞行控制系统和系统仿真。
