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基于补偿神经网络的模糊飞机刹车控制系统研究
引用本文:李潇,吴瑞祥.基于补偿神经网络的模糊飞机刹车控制系统研究[J].计算机仿真,2006,23(1):59-61,119.
作者姓名:李潇  吴瑞祥
作者单位:北京航空航天大学,机械工程及自动化学院,北京,100083
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。

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
文章编号:1006-9348(2006)01-0059-03
收稿时间:2004-10-13
修稿时间:2004-10-13

Development of Aircraft Fuzzy Brake System Based on Compensated Neural Network
LI Xiao,WU Rui-xiang.Development of Aircraft Fuzzy Brake System Based on Compensated Neural Network[J].Computer Simulation,2006,23(1):59-61,119.
Authors:LI Xiao  WU Rui-xiang
Affiliation:School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
Abstract:Although 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.
Keywords:Anti - skid brakes  Nonlinear systems  Neural network  Compensation  Fuzzy control  Intelligent control
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