建模不确定性下变循环发动机自适应控制器设计 *

推进技术 ›› 2018, Vol. 39 ›› Issue (4): 872-880.

建模不确定性下变循环发动机自适应控制器设计 *

李嘉¹,李华聪²,韩小宝²,王淑红³

长安大学道路施工技术与装备教育部重点实验室，陕西西安 710064,西北工业大学动力与能源学院，陕西西安 710072,西北工业大学动力与能源学院，陕西西安 710072,中航工业西安航空动力控制科技有限公司，陕西西安 700077

发布日期:2021-08-15
作者简介:李嘉，博士生，研究领域为航空发动机控制器设计及燃油系统设计。
基金资助:
国家自然科学基金(51506177)。

Adaptive Controller Design with Modeling Uncertainties of Variable Cycle Engine

Key Laboratory of Road Construction Technology and Equipment，Ministry of Education，Chang’an University，Xi’an 710064，China,School of Power and Energy，Northwestern Polytechnical University，Xi’an 710072，China,School of Power and Energy，Northwestern Polytechnical University，Xi’an 710072，China and China AVIC Xi’an Aero-Engine Controls Technology Co.Limited，Xi’an 700077，China

Published:2021-08-15

摘要/Abstract

摘要： 针对变循环航空发动机存在建模不确定情况下的多变量控制器设计问题，给出了一种最优律下的增广模型参考自适应跟踪补偿设计方法，阐明变循环发动机建模不确定性并引出LQR(Linear Quadratic Regulator)基准控制器动态跟踪不足的问题，进而在基准控制器反馈控制结构框架下，分别实现以下技术突破:确定期望闭环动态的参考模型、基于李亚普诺夫函数严格稳定证明下建立存在建模不确定性的自适应律等，最终以达到系统跟踪误差渐进为零的目标，改善系统不确定性的动态跟踪问题。对变循环航空发动机的控制器仿真结果表明:增广模型参考自适应控制方法改善了原LQR基准控制器对存在建模不确定性时的控制问题，有效地实现了控制指令跟踪，达到了所期望的动态响应，且自适应参数一致渐进稳定。同时，各标称点的稳态控制误差均小于0.3%，系统超调量小于0.8%，调节时间小于1s，符合航空发动机控制系统技术要求。

关键词: 变循环航空发动机；多变量控制；建模不确定性；模型参考自适应控制；跟踪补偿

Abstract: As to solve the problem of multivariable controller design with modeling uncertainties of variable cycle engine，an augmented model reference adaptive tracking control compensation design method under the optimal law was given. Firstly，variable cycle engine modeling uncertainties analysis was clarified and lead to the dynamic tracking problem of LQR controller. Then under the based controller feedback structure，reference model with expected closed-loop dynamic performance was determined and the adaptive laws with modeling uncertainties were established under lyapunov function stability proof，which to achieve zero tracking error and eventually improve the dynamic tracing with uncertainties. The simulation results of variable cycle engine controller showed that augmented model reference adaptive control method improved the LQR controller performance with modeling uncertainties，effectively realized the tracking control，reached the expected response performance. The designed adaptive parameters had consistent gradual stability. Meanwhile，at the different state points，the steady control errors were less than 0.3%，overshoot values were less than 0.8%，the adjust times were less than 1s，which satisfies the requirements of the aero engine control system technology.

Key words: Variable cycle engine；Multi-variable control；Modeling uncertainties；MARC；Tracking compensation

李嘉,李华聪,韩小宝,王淑红. 建模不确定性下变循环发动机自适应控制器设计 *[J]. 推进技术, 2018, 39(4): 872-880.

LI Jia¹,LI Hua-cong²,HAN Xiao-baO²,WANG Shu-hong³. Adaptive Controller Design with Modeling Uncertainties of Variable Cycle Engine[J]. Journal of Propulsion Technology, 2018, 39(4): 872-880.

参考文献

[1] 樊思齐. 航空发动机控制[M]. 西安:西北工业大学大学出版社, 2008.
[2] Khalil H. Nonlinear System[M]. Upper Saddle River:Prentice Hall, 1996.
[3] Lavretsky E. 鲁棒自适应控制及航空航天应用[M]. 程锦房, 周浩, 译. 北京:国防工业出版社, 2005.
[4] 韩京清. 自抗扰控制技术—估计补偿不确定因素的控制技术[M]. 北京:国防工业出版社, 2008.
[5] Asha P Nair, Selvaganesan N, Lalithambika V R. Lyapunov Based PD/PID in Model Reference Adaptive Control for Satellite Launch Vehicle Systems[J]. Aerospace Science and Technology, 2016, 12(8): 70-77.
[6] Stepanyan V, Krishnakumar K. State and Output Fedback Certainty Equivalence M-MRAC for Systems with Unmatched Uncertainties[J]. Asian Journal of Control, 2015, 17(6): 2041-2054.
[7] 周涛, 王磊. 基于跟踪微分器的模型参考自适应控制[J]. 电光与控制, 2012, 19(10): 46-49.
[8] 张维存, 刘冀伟, 胡广大. 鲁棒多模型自适应控制系统的稳定性[J]. 自动化学报, 2015, 1(5): 113-121.
[9] 张福海, 付宜利, 王树国. 惯性参数不确定的自由漂浮空间机器人自适应控制研究[J]. 航空学报, 2012, 33(12): 2347-2354.
[10] Ma JING, ZHANG Renhua. Model Reference Adaptive Neural Sliding Mode Control for Aero-Engine[J]. AASRI Procedia, 2012, (3): 508-514.
[11] 王曦, 曾庆福. 航空发动机结构参数和非结构参数不确定系统鲁棒[H∞]输出反馈控制[J]. 航空动力学报, 1999, 14(3): 305-309.
[12] 朱玉斌, 樊思齐, 张秀华, 等. 基于自调整神经元的航空发动机多变量自适应解耦控制[J]. 航空动力学报, 2007, 22(3): 490-494.
[13] 吴沧浦. 最优控制的理论与方法[M]. 北京:国防工业出版社, 2000.
[14] Labane Chrif, Zemalache Meguenni Kadda. Aircraft Control System Using LQG and LQR Controller with Optimal Estimation-Kalman Filter Design[J]. Procedia Engineering, 2014, 80: 245-257.
[15] Anton V Proskurnikov. Universal Controllers of V.A.Yakubovich: a Systematic Approach to LQR Problems with Uncertain External Signals[J]. IFAC-Papers Online, 2015, 11(48): 557-562.
[16] Maity A, Hocht L, Holzapfel F. Higher Order Direct Model Reference Adaptive Control with Generic Uniform Ultimate Boundedness[J]. International Journal of Control, 2015, 88/10: 2126-2142.
[17] Alexander W, Zhllitsch. Application of Adaptive Control with Closed-Loop Reference Models to a Model Aircraft with Actuator Dynamics and Input Uncertainty[C].Chicago: American Control Conference (ACC), 2015.
[18] Nguyen N T. Optimal Control Modification for Robust Adaptive Control with Large Adaptive Gain[J]. Systems & Control Letters, 2012, 61(4): 485-494.
[19] Kamalasadan S. A Neural Network Parallel Adaptive Controller for Fighter Aircraft Pitch-Rate Tracking[J]. IEEE Transactions on Instrumentation and Measurement, 2011, 60(1): 258-267.
[20] 卢彬彬, 肖玲斐, 龚仁吉, 等. 基于人工蜂群算法的航空发动机参数自整定PID控制[J]. 推进技术, 2015, 36(1): 130-135. (LU Bin-bin, XIAO Ling-fei, GONG Ren-ji, et al. Self-Tuning PID Control for AeroEngine Based on Artificial Bee Colony Algorithm[J]. Journal of Propulsion Technology, 2015, 36(1).)
[21] 张海波, 王健康, 王日先, 等. 一种航空发动机多变量自抗扰解耦控制律设计[J]. 推进技术, 2012, 33(1): 78-83. (ZHANG Hai-bo, WANG Jian-kang, WANG Ri-xian, et al. Design of an Active Disturbance Rejection Decoupling Multivariable Control Scheme for Aero-Engine[J]. Journal of Propulsion Technology, 2012, 33(1).)(编辑:朱立影)　　　　　　　　　　　　　*　收稿日期:2016-08-12；修订日期:2016-09-28。基金项目:国家自然科学基金(51506177)。作者简介:李嘉,博士生,研究领域为航空发动机控制器设计及燃油系统设计。E-mail: lijia89626@163.com