[1]张昊 陈自力 齐晓慧.基于RBF神经网络PID的无人动力伞控制[J].计算机技术与发展,2012,(02):206-209.
　ZHANG Hao,CHEN Zi-li,QI Xiao-hui.Unmanned Powered Parachute Aircraft Control Based on RBF Neural Network PID[J].,2012,(02):206-209.
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基于RBF神经网络PID的无人动力伞控制()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年02期
页码:
206-209
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Unmanned Powered Parachute Aircraft Control Based on RBF Neural Network PID
文章编号:
1673-629X（2012）02-0206-04
作者:
张昊 陈自力 齐晓慧
军械工程学院光学与电子工程系
Author(s):
ZHANG Hao; CHEN Zi-li; QI Xiao-hui
Department of Optical and Electrics Engineering,Ordnance Engineering College
关键词:
RBF神经网络; PID控制; 无人动力伞
Keywords:
RBF network;  PIDcontrol;  unmanned powered parachute
分类号:
TP39
文献标志码:
A
摘要:
动力伞是一个复杂的非线性动力学对象,难以用精确的数学模型描述。对于这种具有非线性、时变和强耦合特性的综合系统,采用传统PID控制方法不能得到满意的控制效果,因此提出一种基于RBF神经网络的PID控制方法。该方法利用RBF神经网络的自学习、自适应能力自调整系统的控制参数,从而实现对PID控制器各参数的优化整定。在Mat-lab软件中的仿真结果表明,该方法可实现对动力伞有效的控制,并且与传统PID相比,具有更短的调节时间,更好的稳定性、自适应性和鲁棒性
Abstract:
Unmanned powered parachute aircraft is a complicated nonlinear dynamics object.It is difficult to describe by precise mathematical model.For the integrated system with nonlinear time-varying and strong coupling characters,since it cannot acquire the satisfied control result using the traditional PID control method,a self-turning PID control strategy based on RBF network is put forward in this paper.This method uses the ability of self-study and self-adaptability of RBF network to turn parameters of system,accordingly,realizes the setting of PID controller parameters.Simulation result in Matlab indicates that it can get satisfied control result,shorter adjusting time,better stability,better self-adaptability and robustness using this method

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备注/Memo

备注/Memo:
国防武器装备预研基金项目（9140A25070509JB3405）张昊（1988-），男，山西临汾人，硕士研究生，主要从事无人动力伞控制研究
更新日期/Last Update: 1900-01-01