摘要
尽管飞机防滑刹车可以在保持可操纵性的同时优化刹车效率,但遇到不同路况时刹车性能却时常下降。为了在防滑的同时获得最大的刹车结合系数,该文提出了新的飞机防滑刹车控制律：基于补偿神经网络的模糊控制。控制器识别飞机和机轮的速度反馈,从而调整刹车力矩实现优化刹车。同时系统又可根据复杂的路况,通过补偿神经网络进行自优化。通过MATLAB、VC仿真得出滑移率跟踪曲线。结果表明刹车系统在适应不同路况时有很好的控制性能。
Ahhough aircraft antiskid brake system is designed to optimize braking effectiveness while maintaining steerability, its performance often degrades for different road conditions. To prevent serious skidding and obtain maximum friction coefficient in different conditions, a novel law of anti - skid control for aircraft is presented ： fuzzy control based on compensated neural network. The controller described here identifies the runway condition from the aircraft and the wheel responses, and modulates the brake torque for optimum braking. Meanwhile, the whole system is optimized using compensated neural network for hash road conditions. Simulation results confirm the satisfactory performance of the controller in adapting to different runway conditions.
出处
《计算机仿真》
CSCD
2006年第1期59-61,119,共4页
Computer Simulation
关键词
防滑刹车系统
非线性系统
神经网络
补偿
模糊控制
智能控制
Anti - skid brakes
Nonlinear systems
Neural network
Compensation
Fuzzy control
Intelligent control
