摘要
航空业的发展对飞机防滑刹车系统提出了更高的要求,而传统PID+PBM控制器存在着低速打滑、刹车效率较低等问题;针对刹车过程中的不确定性和非线性问题,提出采用T-S模糊神经网络来进行防滑刹车控制器设计;在MATLAB/SIMULINK平台建立飞机刹车总体仿真模型,将设计的控制器与传统控制器进行对比仿真试验;仿真结果表明,基于T-S模糊神经网络的控制器解决了传统PID+PBM系统存在的问题,具有良好的控制效果,系统具有鲁棒性,能够适应变化的跑道情况,为飞机防滑刹车控制提供了一种新的方法。
Development of aircraft industry has proposed high demand of aircraft antiskid braking system,while the traditional PID＋PBM brake control system has the problem of low braking efficiency and low speed skid.Considering the nonlinearity and uncertainty of braking process,paper designs antiskid braking controller based on T-S fuzzy neural network.The numeric model of the proposed system and the new control algorithm has been verified and simulated in MATLAB/SIMULINK software.The simulation results show that the T-S fuzzy neural network controller solves the problem of traditional controller,improves the brake performance,has good robustness,and provides a new way for controlling antiskid braking system.
出处
《计算机测量与控制》
北大核心
2014年第11期3576-3580,共5页
Computer Measurement &Control
基金
国家高技术研究发展计划(863重点计划)资助项目(2009AA034300)
