Performance seeking control of aero-engine based on nonlinear model prediction
-
摘要:
提出一种基于非线性模型预测的航空发动机性能寻优控制方法，以提升性能寻优控制的响应速度。基于风扇进口温度插值的复合推进系统动态模型建模方法建立全包线机载预测模型，以实时估计发动机性能参数及有限时域内的未来输出；基于非线性模型预测控制方法，将最大推力模式、最小油耗模式、最低涡轮温度模式3种性能寻优控制模式转化为实时动态性能寻优问题，并设计相应实时控制的性能指标，提升发动机响应速度。仿真结果表明：相比于传统方法，所提出方法建立的机载模型在3种性能寻优控制模式下有较好的控制效果且响应速度提升0.5～5 s，在高空巡航工作点，最大推力模式下推力提高19.8%，最小耗油模式下耗油率下降3.12%，最低涡轮前温度模式下涡轮前温度下降17 K，验证了控制方法的有效性。
-
关键词:
- 航空发动机控制 /
- 非线性模型预测控制 /
- 性能寻优控制 /
- 复合推进系统动态模型 /
- 机载模型
Abstract:To improve the response speed of aero-engine performance seeking control, an aero-engine performance seeking control method based on nonlinear model prediction control was proposed. The full envelope interpolation compact propulsion system dynamic model was used as the on-board model to estimate the engine performance parameters and the future outputs of the limited time domain. With the nonlinear model prediction control method, three typical performance seeking control modes, i.e.: the maximum thrust mode, the minimum fuel consumption mode and the minimum turbine temperature mode were changed into real-time performance seeking, and corresponding real-time control performance indexes were designed to improve engine response speed. The simulation results showed that compared with the traditional method, the proposed control method had better control effect under three performance optimization control modes, and the response speed increased from 0.5 s to 5 s. At the high altitude cruising working point the thrust of the maximum thrust mode increased by 19.8%; the fuel consumption rate of the minimum fuel consumption mode dropped by 3.12%; the temperature of the minimum turbine temperature mode dropped by 17 K, helping to verify the effectiveness of the control method.
-
图 9 H=9 km, Ma=0.8最大推力仿真
Figure 9. The maximum thrust mode simulation at H=9 km, Ma=0.8
图 10 H=9 km, Ma=0.8最小耗油模式仿真
Figure 10. The minimum fuel consumption mode simulation at H=9 km, Ma=0.8
图 11 H=9 km, Ma=0.8最低涡轮前温度模式仿真
Figure 11. The minimum pre-turbine temperature mode simulation at H=9 km, Ma=0.8
表 1 10个典型工作点
Table 1. Ten typical working points
高度H/km 马赫数Ma 风扇进口总温Tt2/K 0 0 288.15 9 0.8 259.0452 9 0.9 266.8533 9 0.99 274.6660 9 1.05 280.2878 9 1.2 295.7892 9 1.3 307.2717 9 1.4 319.6728 9 1.6 347.2308 9 1.9 395.4573 
下载: 导出CSV
表 2 PSC约束
Table 2. Constraints of PSC
约束变量 下约束边界 上约束边界 Wfb/（kg/s） 2.8 0.45 dWfb/（kg/s2） −0.02 0.02 A8/m2 0.24 0.32 dA8/（m2/s） −0.005 0.005 Nf/% 102 102 Nc/% 102 102 Smf 0.12 Smc 0.12 T4/K 1 870
下载: 导出CSV
-
[1] STEWART J. Integrated flight propulsion control research results using the NASA F-15 HIDEC flight research facility[R]. AIAA-1992-4106, 1992. [2] WURTH S, MAHONE T, HART J, et al. X-35B integrated flight propulsion control fault tolerance development[R]. AIAA-2002-6019, 2002. [3] ORME J S, NOBBS S G. Maximum thrust mode evaluation[R]. N95-33017, 1995. [4] ORME J S, NOBBS S G. Minimum fuel mode evaluation[R]. N95-33015, 1995. [5] ORME J S, NOBBS S G. Minimum fan turbine inlet temperature mode evaluation[R]. N95-33016, 1995. [6] GUO T H, LITT J. Resilient propulsion control research for the NASA integrated resilient aircraft control (IRAC) project[R]. AIAA-2007-2802, 2007. [7] GUO T H, LITT J. Risk management for intelligent fast engine response control[R]. AIAA-2009-1873, 2009. [8] CSANK J, CHIN J, MAY R, et al. Implementation of enhanced propulsion control modes for emergency flight operation[R]. AIAA-2011-1590, 2011. [9] GILYARD G, ORME J. Subsonic flight test evaluation of a performance seeking control algorithm on an F-15 airplane[R]. AIAA-92-3743, 1992. [10] ORME J, GILYARD G. Subsonic flight test evaluation of a propulsion system parameter estimation process for the F100 engine[R]. AIAA-92-3745, 1992. [11] ORME J, GILYARD G. Preliminary supersonic flight test evaluation of performance seeking control[R]. AIAA-93-1821, 1993. [12] ORME J, CONNERS T. Supersonic flight test results of a performance seeking control algorithm on a NASA F-15 spacecraft[R]. AIAA-94-3210, 1994. [13] 袁春飞,孙健国,熊智,等. 飞/推综合控制模式亚声速半物理仿真试验[J]. 推进技术,2003,24(4): 353-356. doi: 10.3321/j.issn:1001-4055.2003.04.018YUAN Chunfei,SUN Jianguo,XIONG Zhi,et al. Subsonic semi-physical simulation test of integrated flight/propulsion control mode[J]. Journal of Propulsion Technology,2003,24(4): 353-356. (in Chinese) doi: 10.3321/j.issn:1001-4055.2003.04.018 [14] 朱之丽,王晓波. 高推重比涡扇发动机性能寻优分析研究[J]. 航空动力学报,1999,14(3): 260-264. doi: 10.3969/j.issn.1000-8055.1999.03.008ZHU Zhili,WANG Xiaobo. Analysis and research on performance optimization of high thrust-to-weight ratio turbofan engine[J]. Journal of Aerospace Power,1999,14(3): 260-264. (in Chinese) doi: 10.3969/j.issn.1000-8055.1999.03.008 [15] 何黎明,樊丁. 利用 SQP 控制涡扇发动机加速过程的多目标最优化研究[J]. 航空动力学报,2001,16(2): 179-181. doi: 10.3969/j.issn.1000-8055.2001.02.018HE Liming,FAN Ding. Multi-objective optimization research of turbofan engine acceleration process controlled by SQP[J]. Journal of Aerospace Power,2001,16(2): 179-181. (in Chinese) doi: 10.3969/j.issn.1000-8055.2001.02.018 [16] 孙丰诚,孙健国. 基于序列二次规划算法的发动机性能寻优控制[J]. 航空动力学报,2005,20(5): 862-867. doi: 10.13224/j.cnki.jasp.2005.05.029SUN Fengcheng,SUN Jianguo. Optimization control of engine performance based on sequential quadratic programming algorithm[J]. Journal of Aerospace Power,2005,20(5): 862-867. (in Chinese) doi: 10.13224/j.cnki.jasp.2005.05.029 [17] 朱玉斌,樊思齐,李华聪,等. 航空发动机性能寻优控制混合优化算法[J]. 航空动力学报,2006,21(2): 421-426. doi: 10.3969/j.issn.1000-8055.2006.02.033ZHU Yubin,FAN Siqi,LI Huacong,et al. Hybrid optimization algorithm for aeroengine performance optimization control[J]. Journal of Aerospace Power,2006,21(2): 421-426. (in Chinese) doi: 10.3969/j.issn.1000-8055.2006.02.033 [18] 任新宇,杨育武,樊思齐. 推进系统综合性能寻优控制研究[J]. 推进技术,2010,31(1): 61-64, 81. doi: 10.13675/j.cnki.tjjs.2010.01.005REN Xinyu,YANG Yuwu,FAN Siqi. Research on optimization control of propulsion system[J]. Journal of Propulsion Technology,2010,31(1): 61-64, 81. (in Chinese) doi: 10.13675/j.cnki.tjjs.2010.01.005 [19] 王健康,张海波,孙健国,等. 基于复合模型及FSQP算法的发动机性能寻优控制试验[J]. 推进技术,2012,33(4): 579-590. doi: 10.13675/j.cnki.tjjs.2012.04.007WANG Jiankang,ZHANG Haibo,SUN Jianguo,et al. Engine performance optimization control test based on compound model and FSQP algorithm[J]. Journal of Propulsion Technology,2012,33(4): 579-590. (in Chinese) doi: 10.13675/j.cnki.tjjs.2012.04.007 [20] 孙丰勇,张海波,叶志锋,等. 航空发动机超声速巡航性能寻优控制研究[J]. 推进技术,2015,36(8): 1248-1256. doi: 10.13675/j.cnki.tjjs.2015.08.019SUN Fengyong,ZHANG Haibo,YE Zhifeng,et al. Research on supersonic cruise performance optimization control of aeroengine[J]. Journal of Propulsion Technology,2015,36(8): 1248-1256. (in Chinese) doi: 10.13675/j.cnki.tjjs.2015.08.019 [21] 王元,李秋红,黄向华. 基于DMOM算法的航空发动机性能寻优控制[J]. 航空动力学报,2016,31(4): 948-954. doi: 10.13224/j.cnki.jasp.2016.04.023WANG Yuan,LI Qiuhong,HUANG Xianghua. Aeroengine performance optimization control based on DMOM algorithm[J]. Journal of Aerospace Power,2016,31(4): 948-954. (in Chinese) doi: 10.13224/j.cnki.jasp.2016.04.023 [22] 杨旦旦. 基于Fibonacci搜索方法的航空发动机性能寻优[J]. 航空动力学报,2016,31(6): 1441-1449. doi: 10.13224/j.cnki.jasp.2016.06.021YANG Dandan. Aeroengine performance optimization based on Fibonacci search method[J]. Journal of Aerospace Power,2016,31(6): 1441-1449. (in Chinese) doi: 10.13224/j.cnki.jasp.2016.06.021 [23] 彭靖波, 田少男, 姚凯翔. 基于GA-FTA算法的航空发动机性能寻优控制研究[C]//中国航空学会. 探索 创新 交流(第7集)−第七届中国航空学会青年科技论坛文集(上册). 北京: 中国科学技术出版社, 2016: 432-436. [24] 聂友伟,李秋红,王元,等. 基于SQCQP算法的变循环发动机性能寻优控制[J]. 北京航空航天大学学报,2017,43(12): 2564-2572. doi: 10.13700/j.bh.1001-5965.2016.0926NIE Youwei,LI Qiuhong,WANG Yuan,et al. Optimal control of variable cycle engine performance based on SQCQP algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics,2017,43(12): 2564-2572. (in Chinese) doi: 10.13700/j.bh.1001-5965.2016.0926 [25] 李勇,韩非非,张昕喆,等. 基于遗传算法-序列二次规划的涡扇发动机最低油耗性能寻优控制[J]. 推进技术,2020,41(7): 1638-1648. doi: 10.13675/j.cnki.tjjs.190455LI Yong,HAN Feifei,ZHANG Xinzhe,et al. Optimal control of minimum fuel consumption performance of turbofan engine based on genetic algorithm-sequential quadratic programming[J]. Journal of Propulsion Technology,2020,41(7): 1638-1648. (in Chinese) doi: 10.13675/j.cnki.tjjs.190455 [26] 金崇文,郑前钢,张海波,等. 基于复合推进系统动态模型-状态变量模型的航空发动机直接推力预测控制[J]. 推进技术,2022,43(1): 354-363. doi: 10.13675/j.cnki.tjjs.200524JIN Chongwen,ZHENG Qiangang,ZHANG Haibo,et al. Predictive control of aero-engine direct thrust based on dynamic model of compound propulsion system-state variable model[J]. Journal of Propulsion Technology,2022,43(1): 354-363. (in Chinese) doi: 10.13675/j.cnki.tjjs.200524 [27] 王健康. 基于机载复合模型及SQP的发动机性能寻优控制研究[D]. 南京: 南京航空航天大学, 2010.WANG Jiankang. Research on engine performance optimization control based on airborne composite model and SQP[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2010. (in Chinese) -
点击查看大图
计量
- 文章访问数: 679
- HTML浏览量: 298
- PDF量: 74
- 被引次数: 0