基于RBF网络的航空发动机 terminal滑模控制

苗卓广; 谢寿生; 王海涛; 翟旭升; 张子阳; 孙晓东

基于RBF网络的航空发动机 terminal滑模控制

1.
空军工程大学工程学院,西安 710038
2.
中国人民解放军 94333部队,潍坊 261051

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出版历程
- 收稿日期: 2009-10-31
- 修回日期: 2010-04-01
- 刊出日期: 2010-12-28

Terminal sliding mode controller for aero-engine based on RBF neural network

1.
The Engineering Institute, Air Force Engineering University,Xian 710038,China
2.
Unit 94333,The Chinese People's Liberation Army,Weifang 261051,China

摘要

摘要: 针对现代航空发动机是一个具有不确定性的强非线性系统,结合滑模控制和神经网络控制的优点,提出了一种基于径向基函数(radical basis function,简称RBF)网络的航空发动机terminal滑模控制方法.分析了传统指数趋近律的不足,提出了一种改进的指数趋近律来削弱抖振.该控制器采用terminal滑模面,并且利用径向基函数神经网络在线实时补偿未知干扰和不确定项的影响.仿真结果表明,所设计的控制器取得了令人满意的控制效果,能有效地抑制干扰和参数不确定性的影响,削弱了抖振.
- 航空发动机 /
- terminal滑模控制 /
- 径向基函数(RBF)神经网络 /
- 抖振 /
- 趋近律
Abstract: A method of terminal sliding mode control was put forward for aero-engine with uncertainty and strong nonlinearity based on radical basis function (RBF) neural network.The method integrated neural network control into sliding mode control.Shortage of traditional exponent reaching law was analyzed,and an improved exponent reaching law was proposed to weaken the chattering.Controller was devised using terminal sliding mode surface.And influence caused by unknown disturbance and uncertainty was compensated by RBF neural network in a real-time manner.Simulation results show that the devised controller has good effect,effectively restrains the influence and weakens the chattering.
- aero-engine /
- terminal sliding mode control /

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参考文献(12)

[1]	董劲,黄金泉.航空发动机多变量模糊PID控制[J].航空动力学报,2003,18(4):538-541. DONG Jin,HUANG Jinquan.Multivariable fuzzy-PID control for aeroengine[J]. Journal of Aerospace Power,2003,18(4):538-541.(in Chinese)
[2]	王永庭,郭迎清,王海泉.增广LQL方法及其在航空发动机控制中的应用[J].航空动力学报,2007,22(1):132-136. WANG Yongting,GUO Yingqing,WANG Haiquan.Augmented LQL method and its application to aeroengine control[J].Journal of Aerospace Power,2007,22(1):132-136.(in Chinese)
[3]	高为炳.变结构控制的理论及设计方法[M].北京:科学出版社,1998.
[4]	Erbatur K,Kawamura A.Chattering elimination via fuz-zy boundary layer tuning //Industrial Electronics Society,IEEE 2002 28th Annual Conference.Sevilla,Spain:IEEE Press,2002,11:2131-2136.
[5]	Jiang K,Zhang J G,Chen Z M.A new approach for the sliding mode control based on fuzzy reaching law //Intelligent Control and Automation,Proceedings of the 4th World Congress.Shanghai,China:Press of University of Science and Technology of China,2002,6:656-660.
[6]	Ha Q P,Nguyen Q H,Rye D C,et al.Fuzzy sliding mode controller with applications[J].IEEE Transaction on Industrial Electronics,2001,48(1):38-41.
[7]	Hamerlain M,Youssef T,Belhocine M.Switching on the derivative of control to reduce chatter[J].IEEE Proceed-ings on Control Theory and Applications,2001,148(1):88-96.
[8]	Man Z H,Yu X H,Eshraghian K,et al.A robust adaptive sliding mode tracking control using an RBF neural net- work for robotic manipulators[J].IEEE International Conference on Neural Network,1995,5:2403-2408.
[9]	Elmali H,Olgac N.Sliding mode control with perturbation estimation (SMCPE):a new approach[J].Int. J. Control,1992,56(4):923-941.
[10]	Venkataraman S T,Gulati S.Control of nonlinear systems using terminal sliding modes[J].Journal of Dynamic Systems,Measurement,and Control,1993,115(3):554-560.
[11]	谢寿生.某型加力涡扇发动机[M].西安:空军工程大学,2002. XIE Shousheng.A certain afterburning turbofan engine[M].Xian:Air Force Engineering University,2002.(in Chinese)
[12]	李彬,孙晓东,劭汉永.航空发动机模糊滑模变结构控制研究[J].电光与控制,2008,15(12):47-50. LI Bin,SUN Xiaodong,SHAO Hanyong.Study on fuzzy sliding mode variable structure control for aeroengine[J].Electronics Optics and Control,2008,15(12):47-50.(in Chinese)