| 基于无味卡尔曼滤波的飞机防滑刹车模糊神经网络控制 |
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| 引用本文： | 刘文胜,王霞,马运柱,陈梦樵.基于无味卡尔曼滤波的飞机防滑刹车模糊神经网络控制[J].航空精密制造技术,2017,53(2). |
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| 作者姓名： | 刘文胜 王霞 马运柱 陈梦樵 |
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| 作者单位： | 中南大学 粉末冶金国家重点实验室,长沙,410083 |
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| 基金项目： | 国家高技术研究发展计划 |
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| 摘 要： | 根据对飞机刹车过程动力学分析与建模,本文提出了一种基于无味卡尔曼滤波(UKF)的模糊神经网络控制律。本控制律结合了无味卡尔曼滤波对机体速度的良好估计效果和模糊神经网络控制器对不同系统参数的适应能力,能够很好完成对最佳滑移率的追踪任务。Matlab仿真试验结果显示,基于无味卡尔曼滤波的模糊神经网络控制器可以准确的估计飞机滑跑时的速度,改善飞机防滑刹车系统性能,提高刹车效率。
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| 关 键 词： | 飞机防滑刹车 滑移率 无味卡尔曼 T-S模糊神经网络 |
A Fuzzy Neural Network Control of Anti-Skid Braking System Based on Unscented Kalman Filter (UKF) |
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| Abstract: | According to the force analysis of the body and the motion, the nonlinear dynamic model and propose a fuzzy neural network control was presented based on unscented Kalman filter estimate algorithm. FNN controller has good parameter adaptive ability. Using the aircraft system state estimated by UKF as the inputs, FNN controller can rapid track the optimal slip ratio. Matlab simulation showed that FNN control based on UKF estimate algorithm can accurate estimate the aircraft velocity, improve the aircraft braking performance and efficiency. |
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| Keywords: | anti-skidbraking slip ratio unscented Kalman filter T-S fuzzy neural network |
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