基于神经网络自适应动态逆的结冰飞机飞行安全边界保护方法

魏扬; 徐浩军; 薛源; 郑无计; 李哲; 裴彬彬

doi:10.7527/S1000-6893.2018.22488

航空学报 >

2019 , Vol. 40 >Issue 5: 122488 - 122488

DOI: https://doi.org/10.7527/S1000-6893.2018.22488

流体力学与飞行力学

基于神经网络自适应动态逆的结冰飞机飞行安全边界保护方法

魏扬 ,
徐浩军 ,
薛源 ,
郑无计 ,
李哲 ,
裴彬彬

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1. 空军工程大学航空工程学院, 西安 710038;
2. 空军石家庄飞行学院第四训练旅, 保定 074212

收稿日期: 2018-06-27

修回日期: 2018-07-18

网络出版日期: 2018-09-19

基金资助

国家"973"计划（2015CB755802）；国家自然科学基金（61503406）；民用飞机专项研究（MJ-2015-F-019）

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Aircraft flight safety envelope protection under icing conditions based on adaptive neural network dynamic inversion

WEI Yang ,
XU Haojun ,
XUE Yuan ,
ZHENG Wuji ,
LI Zhe ,
PEI Binbin

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1. Aeronautics Engineering College, Air Force Engineering University, Xi'an 710038, China;
2. Fourth Training Brigade, Shijiazhuang Flighting College of Air Force, Baoding 074212, China

Received date: 2018-06-27

Revised date: 2018-07-18

Online published: 2018-09-19

Supported by

National Basic Research Program of China (2015CB755802); National Natural Science Foundation of China (61503406); Civil Aircraft Special Research (MJ-2015-F-019)

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摘要

考虑到飞机带冰飞行的安全问题，对结冰飞机进行安全边界保护成为一种有效的解决手段。基于神经网络自适应动态逆跟踪性能好、鲁棒性强的优点，提出了以安全关键飞行参数限制值作为神经网络自适应动态逆的输入，获取可用舵面偏转角的边界保护方法。建立了飞机本体动力学模型，采用高精度的数值模拟方法获得结冰数据库。设计了神经网络自适应动态逆控制律，通过在动态逆环节引入单隐层神经网络，对不确定性逆误差进行自适应补偿，增强了控制系统的鲁棒性。以俯仰姿态保持模式为例设计了结冰飞行闭环安全边界保护系统。以结冰飞机最小平飞速度的估算值作为飞机最低飞行速度，设计自动油门控制系统，实现对飞行速度的保护。通过仿真验证了设计的控制律具有较强的鲁棒性。对结冰严重程度线性增加情形下飞机状态参数的动态响应进行了分析。仿真结果表明，所设计的结冰边界保护系统，能够实现飞机在容冰飞行过程中对安全关键参数如迎角、飞行速度的实时保护。

关键词： 飞机结冰; 边界保护; 神经网络自适应动态逆; 俯仰姿态保持; 安全关键参数

本文引用格式

魏扬 , 徐浩军 , 薛源 , 郑无计 , 李哲 , 裴彬彬 . 基于神经网络自适应动态逆的结冰飞机飞行安全边界保护方法[J]. 航空学报, 2019 , 40(5) : 122488 -122488 . DOI: 10.7527/S1000-6893.2018.22488

Abstract

Flight safe envelope protection of iced aircraft has become an effective solution to the flight safety under icing conditions. Based on the good tracking performance and strong robustness of the adaptive neural network dynamic inversion control, an envelope protection method is proposed to obtain the available deflection angle of control surface by using the limit value of the key flight safety parameters as input of control loop. The dynamic model of the aircraft is established, and a high precision numerical simulation method is used to obtain the icing aerodynamic database. The adaptive neural network dynamic inversion control law for an aircraft is designed. By introducing the single hidden layer neural network in dynamic inversion, the uncertainty inverse error is compensated adaptively, and the robustness of the control system is enhanced. The closed loop envelope protection system in pitch attitude hold mode under icing conditions is designed. An automatic throttle control system is designed on the assumption that the minimum flying speed is the same as the estimated value of the minimum level of the flight speed and the design is used to protect the flight speed. The simulation results show that the designed control law has strong robustness. The dynamic response of the aircraft state parameters is analyzed in the case of the linear increase of icing severity. The simulation results show that the designed envelope protection system can realize the real-time protection of the key security parameters such as the angle of attack and the speed during the ice-tolerant flight.

Key words： aircraft icing; envelope protection; adaptive neural network dynamic inversion; pitch attitude hold; key security parameters

参考文献

[1] BRAGG M B, PERKINS W R, SARTER N B, et al. An interdisciplinary approach to inflight aircraft icing safety:AIAA-1998-0095[R]. Reston, VA:AIAA, 1998.
[2] BRAGG M B, BASAR T, PERKINS W R, et al. Smart icing systems for aircraft icing safety:AIAA-2002-0813[R]. Reston, VA:AIAA, 2002.
[3] SHARMA V, VOULGARIS P G. Aircraft Autopilot analysis and envelope protection for operation under icing conditions[J]. Journal of Guidance, Control and Dynamics, 2004, 27(3):454-465.
[4] MERRET J M, HOSSAIN K N, BRAGG M B. Envelope protection and atmospheric disturbances in icing encounters:AIAA-2002-0814[R]. Reston, VA:AIAA, 2002.
[5] HOSSAIN K N, SHARMA V, BRAGG M B, et al. Envelope protection and control adaptation in icing encounters:AIAA-2003-0025[R]. Reston, VA:AIAA, 2003.
[6] GINGRAS D R, BARNHART B, RANAUDO R, et al. Envelope protection for in-flight ice contamination:AIAA 2009-1458[R]. Reston, VA:AIAA, 2009.
[7] GINGRAS D R, BARNHART B, RANAUDO R, et al. Development and implementation of a model-driven envelope protection system for in-flight ice contamination:AIAA-2010-8141[R]. Reston, VA:AIAA, 2010.
[8] RANAUDO R, MARTOS B, NORTON B, et al. Piloted simulation to evaluate the utility of a real time envelope protection system for mitigating in-flight icing hazards:AIAA-2010-7987[R]. Reston, VA:AIAA, 2010.
[9] MARTOS B, RANAUDO R, NORTON B, et al. Development, implementation, and pilot evaluation of a model-driven envelope protection system to mitigate the hazard of in-flight ice contamination on a twin-engine commuter aircraft:NASA/CR-2014-218320[R]. Washington, D. C.:NASA, 2014.
[10] LOMBAERTS T, LOOYE G, CHU P, et al. Pseudo control hedging and its application for safe flight envelope protection[C]//AIAA Guidance, Navigation, and Control Conference. Reston, VA:AIAA, 2010.
[11] YAVRUCUK I, PRASAD J V R, UNNIKRISHNAN S. Envelope protection for autonomous unmanned aerial vehicles[J]. Journal of Guidance, Control, and Dynamics, 2009, 32(1):248-261.
[12] LOMBAERTS T, LOOYE G, ELLERBROEK J, et al. Design and piloted simulator evaluation of adaptive safe flight envelope protection algorithm[C]//AIAA Guidance, Navigation, and Control Conference. Reston, VA:AIAA, 2016.
[13] 张智勇. 结冰飞行动力学特性与包线保护控制律研究[D]. 南京:南京航空航天大学, 2006. ZHANG Z Y. Research on iced aircraft flight dynamics characteristics and envelope protection control law[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2006(in Chinese).
[14] 应思斌, 艾剑良. 飞机结冰包线保护对开环飞行性能影响与仿真[J]. 系统仿真学报, 2010, 22(10):2273-2301. YING S B, AI J L. Simulation of aircraft flight envelope protect in icing encounters effects on open loop dynamic[J]. Journal of System Simulation, 2010, 22(10):2273-2301(in Chinese).
[15] 应思斌. 飞机容冰飞行控制系统设计的理论与方法研究[D]. 上海:复旦大学, 2010. YING S B. Research on theory and method of aircraft ice-tolerant flight control system design[D]. Shanghai:Fudan University, 2010(in Chinese).
[16] 周莉, 徐浩军, 杨哲, 等. 飞机在结冰条件下的最优边界保护方法[J]. 上海交通大学学报, 2013, 47(8):1217-1221. ZHOU L, XU H J, YANG Z, et al. Optimal boundary protection method for aircraft under icing conditions[J]. Journal of Shanghai Jiao Tong University, 2013, 47(8):1217-1221(in Chinese).
[17] 屈亮, 李颖晖, 袁国强, 等. 基于相平面法的结冰飞机纵向非线性稳定域分析[J]. 航空学报, 2016, 37(3):865-872. QU L, LI Y H, YUAN G Q, et al. Longitudinal nonlinear stabilizing region for icing aircraft based on phase-plane method[J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(3):865-872(in Chinese).
[18] 郑无计, 李颖晖, 屈亮, 等. 基于正规形法的结冰飞机着陆阶段非线性稳定域[J]. 航空学报, 2017, 38(2):520714. ZHENG W J, LI Y H, QU L, et al. Nonlinear stability region of icing aircraft during landing phase based on normal form method[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(2):520714(in Chinese).
[19] BRAGG M, HUTCHISON T, MERRET J. Effect of ice accretion on aircraft flight dynamics[C]//38th AIAA Aerospace Sciences Meeting & Exhibit. Reston, VA:AIAA, 2000.
[20] SONNEVELDT L. Nonlinear F-16 model description[R]. Delft:Delft University of Technology, 2010.
[21] COOK M V. Flight dynamics principles[M]. Burlington, MA:Butterworth-Heinemann, 2007:66-95.
[22] 刘世前. 现代飞机飞行动力学与控制[M]. 上海:上海交通大学出版社, 2014:145-150. LIU S Q. Flight dynamics and control of modern aircrafts[M]. Shanghai:Shanghai Jiao Tong University Press, 2014:145-150(in Chinese).
[23] HUESCHEN R M. Development of the transport class model(TCM) aircraft simulation from a sub-scale generic transport model(GTM) simulation:NASA/TM-2011-217169[R]. Washington, D. C.:NASA, 2011.
[24] HANKE C R, NORDWALL D R. The simulation of a jumbo jet transport aircraft. Volume 2:Modeling data/detail:NASA-CR-114494[R]. Washington, D. C.:NASA, 1970.
[25] NAKWAN K. Improved methods in neural network-based adaptive output feedback control, with applications to flight control[D]. Atlanta, GA:Georgia Institute of Technology, 2003.
[26] JOHNSON E, KANNAN S. Adaptive flight control for an autonomous unmanned helicopter[C]//AIAA Guidance, Navigation, & Control Conference. Reston, VA:AIAA, 2002.

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