Direct thrust control for variable cycle engine based on fractional order PID-nonlinear model predictive control under off-nominal operation conditions

被引:7
作者
Wang, Yangjing [1 ]
Pan, Muxuan [1 ]
Zhou, Wenxiang [1 ]
Huang, Jinquan [1 ,2 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Energy & Power Engn, 29 Yudao St, Nanjing 210016, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, State Key Lab Mech & Control Aerosp Struct, 29 Yudao St, Nanjing 210016, Peoples R China
关键词
Variable cycle engine; Direct thrust control; Fractional order PID-nonlinear model predic-; tive control; Random forest; Long short-term memory; Limit protection;
D O I
10.1016/j.ast.2023.108726
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
With the development and complexity of aero-engines, aero-engine control has been transformed to provide proper thrust and limit protection function under the framework of multivariable control. The multi-operating modes and multi-control variables of the variable cycle engine (VCE) lead to the complex and changeable conversion between measurable variables and thrust, making the traditional indirect thrust control hard to ensure the accuracy and safety of thrust control in different operation conditions. In this paper, a direct thrust control method based on fractional order PID-nonlinear model predictive control (FOPID-NMPC) algorithm is proposed to achieve the tracking of thrust and the limitation of parameters of the VCE under nominal and offnominal operation conditions. In view of the existing thrust estimator designs which are only suitable for nominal conditions, the individual differences and performance degradation are fully investigated. After setting the label which represents degradation mode and constructing the health index which represents degradation degree instead of estimating health parameters directly, a dual margin degradation pattern classifier is constructed based on random forest (RF), and a long short-term memory (LSTM) neural network-based thrust estimator is designed to jointly constitute the estimation module. Then, FOPID and NMPC are combined to ameliorate the control quality and ensure the accuracy and security of thrust control at different operating conditions. This method can escape from local optimum when solving multi-extremum optimization problems. The comparative simulation of the proposed FOPID-NMPC with PID-NMPC and NMPC is performed and the influence of controller parameters on thrust response is explored. Simulations show that the designed controller has better dynamic performance, and also has good steady-state performance and safety.
引用
收藏
页数:20
相关论文
共 37 条
[1]  
Adibhatla S., 1997, P 33 JOINT PROP C EX
[2]  
Adibhatla S., 1992, P 28 JOINT PROP C EX
[3]  
Chatterjee S., 2003, P AIAA GUID NAV CONT, P1
[4]   A novel direct performance adaptive control of aero-engine using subspace-based improved model predictive control [J].
Chen, Qian ;
Sheng, Hanlin ;
Zhang, Tianhong .
AEROSPACE SCIENCE AND TECHNOLOGY, 2022, 128
[5]   Battery Health Prognosis Using Brownian Motion Modeling and Particle Filtering [J].
Dong, Guangzhong ;
Chen, Zonghai ;
Wei, Jingwen ;
Ling, Qiang .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (11) :8646-8655
[6]   Multivariable Sliding-Mode Strategy with Output Constraints for Aeroengine Propulsion Control [J].
Du, Xian ;
Richter, Hanz ;
Guo, Yingqing .
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2016, 39 (07) :1631-1642
[7]  
Garg S., 2007, NASA 20070010763
[8]   Model-based on-board turbofan thrust estimation [J].
Henriksson, Mattias ;
Gronstedt, Tomas ;
Breitholtz, Claes .
CONTROL ENGINEERING PRACTICE, 2011, 19 (06) :602-610
[9]   Improvement of Min-Max limit protection in aircraft engine control: An LMI approach [J].
Imani, Amin ;
Montazeri-Gh, Morteza .
AEROSPACE SCIENCE AND TECHNOLOGY, 2017, 68 :214-222
[10]  
Jeffrey J.B., 2005, NASA/TM-2005-213414