基于松弛约束Hammerstein非线性模型的增程式APU预测控制

赵家豪; 魏民祥; 丁玉章; 沙朝

doi:10.13224/j.cnki.jasp.20210023

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基于松弛约束Hammerstein非线性模型的增程式APU预测控制

自动控制 | 更新时间：2025-04-07

- 基于松弛约束Hammerstein非线性模型的增程式APU预测控制
- Predictive control of extended⁃range APU based on relaxed constrained Hammerstein nonlinear model
- 航空动力学报 2022年37卷第6期页码：1314-1326
- 作者机构：
  
  南京航空航天大学能源与动力学院，南京 210016
- 作者简介：
  
  赵家豪（1996-），男，硕士，主要从事增程式动力系统控制研究。E⁃mail：DC_zjh@outlook.com
- 基金信息：
  
  国防预研项目(513250203)
- DOI：10.13224/j.cnki.jasp.20210023
  中图分类号：
- 稿件说明：
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赵家豪, 魏民祥, 丁玉章, 等. 基于松弛约束Hammerstein非线性模型的增程式APU预测控制[J]. 航空动力学报, 2022,37(6):1314-1326.

Jiahao ZHAO, Minxiang WEI, Yuzhang DING, et al. Predictive control of extended⁃range APU based on relaxed constrained Hammerstein nonlinear model[J]. Journal of Aerospace Power, 2022, 37(6): 1314-1326.
赵家豪, 魏民祥, 丁玉章, 等. 基于松弛约束Hammerstein非线性模型的增程式APU预测控制[J]. 航空动力学报, 2022,37(6):1314-1326. DOI： 10.13224/j.cnki.jasp.20210023.

Jiahao ZHAO, Minxiang WEI, Yuzhang DING, et al. Predictive control of extended⁃range APU based on relaxed constrained Hammerstein nonlinear model[J]. Journal of Aerospace Power, 2022, 37(6): 1314-1326. DOI： 10.13224/j.cnki.jasp.20210023.

摘要

针对增程式辅助动力单元（APU）工作点切换过程的转速控制，提出了一种基于Hammerstein非线性模型的预测控制策略。通过稀疏最小二乘支持向量机⁃自适应混沌粒子群优化（SLSSVM⁃ACPSO）算法辨识激励响应数据建立了发动机Hammerstein非线性模型，在模型预测控制求解最优控制序列时，采用松弛因子松弛约束边界，并设计了有效集（ASM）⁃ACPSO组合算法求解，在控制过程中应用了变预测时域策略。建立系统仿真模型，仿真结果显示：在热机点切换至低负荷点及低负荷点切换至中负荷点的过程中稳定时间分别为2.57 s和2.77 s，转速最大超调率分别为2%和1.6%，均优于两种对比策略；在中负荷点向高负荷点切换过程中，转速超调率较大，但控制过程转矩变化更平缓。仿真结果表明模型预测控制策略控制APU系统转速响应快、转速超调率小，发动机转矩超调量小，具有良好的动态控制效果。

Abstract

In view of the speed control of the working point switching process of the extended⁃range auxiliary power unit （APU），a predictive control strategy based on the Hammerstein nonlinear model was proposed.The excitation data were identified by sparse least squares support vector machine⁃adaptive chaotic particle swarm optimization （SLSSVM⁃ACPSO） algorithm，and the Hammerstein nonlinear model of engine was established.When solving the optimal control sequence in model predictive control，the relaxation factor was used to relax the constraint boundary，and the active set method （ASM）⁃ACPSO combination algorithm was used to obtain the solution.The variable predictive time domain strategy was applied in the control process.The system simulation model was established，and the simulation results showed that in the processes of switching from the warming⁃up point to low load point and from the low load point to the medium load point，the stabilization times were 2.57 s and 2.77 s respectively，and the speed overshoot rates were 2% and 1.6% respectively，which were better than the two comparison strategies.In the process of switching from medium load point to the high load point，the speed overshoot rate was relatively larger，but the change of torque was more smooth in the control process.The simulation result showed that the model predictive control strategy for APU system had fast speed response，small speed and torque overshoot rate，and exhibited good dynamic control effect.

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references

LI J , ZHOU L , ZHOU W . A control strategy to reduce fuel consumption of APU for range‑extended electric vehicle [C]∥ Proceedings of 2nd International Conference on Electronic & Mechanical Engineering and Information Technology . Paris : Atlantis Press , 2012 : 2132 ⁃ 2136 .

RODRIGUES M , KING S , SCOTT D , et al . Advanced energy management strategies for range extended electric vehicle [R]. SAE Technical Paper,2015⁃26⁃0121 ， 2015 .

申永鹏 , 王耀南 , 孟步敏 , 等 . 增程式电动汽车增程器转速切换/功率跟随协调控制 [J]. 中国机械工程 , 2015 , 26 （ 12 ）: 1690 ⁃ 1696 .

SHEN Yongpeng , WANG Yaonan , MENG Bumin , et al . Cooperative control strategy of power following‑speed switching in a range extender electric vehicle APU [J]. China Mechanical Engineering , 2015 , 26 （ 12 ）: 1690 ⁃ 1696 . （in Chinese）

WANG H , WANG L , LIAO Y , et al . Research on engine speed control system based on fuzzy adaptive PID controller [J]. Manufacturing Technology , 2019 , 19 （ 6 ）: 1080 ⁃ 1087 .

康铭鑫 , 李长平 , 刘腾飞 . 基于观测器的发动机转矩跟踪模型预测控制 [J]. 控制与决策 , 2020 , 35 （ 4 ）: 791 ⁃ 798 .

KANG Mingxin , LI Changping , LIU Tengfei . Observer based model predictive torque tracking control for gasoline engines [J]. Control and Decision , 2020 , 35 （ 4 ）: 791 ⁃ 798 . （in Chinese）

陈林林 , 魏民祥 , 邵金菊 . 无人直升机发动机恒转速广义预测控制 [J]. 电子科技大学学报 , 2010 , 39 （ 3 ）: 475 ⁃ 480 .

CHEN Linlin , WEI Minxiang , SHAO Jinju . Generalized predictive controller design for an unmanned helicopter engine speed [J]. Journal of University of Electronic Science and Technology of China , 2010 , 39 （ 3 ）: 475 ⁃ 480 . （in Chinese）

朱徐峰 . 基于预测控制的发动机转速控制策略研究 [D]. 哈尔滨 : 哈尔滨工程大学 , 2017 .

ZHU Xufeng . Study of engine speed control strategy based on predictive control [D]. Harbin : Harbin Engineering University , 2017 . （in Chinese）

WANG Y , ZHENG Q , ZHANG H , et al . A study on nonlinear model predictive control for helicopter/engine with variable rotor speed based on linear Kalman filter [EB/OL].[ 2019‑12⁃30 ]. https:∥doi.org/10.1515/tjj-2019-0016 https://doi.org/10.1515/tjj-2019-0016 .

MEHER T , MAJHI S . Relay based identification of Hammerstein model [J]. International Journal of Dynamics and Control , 2018 , 6 （ 4 ）: 1599 ⁃ 1607 .

潘蕾 , 赵德材 , 张俊礼 , 等 . 微燃机⁃冷热电联供机组的Hammerstein模型及非线性广义预测控制 [J]. 东南大学学报（自然科学版） , 2017 , 47 （ 3 ）: 500 ⁃ 505 .

PAN Lei , ZHAO Decai , ZHANG Junli , et al . Hammerstein model and nonlinear generalized predictive control of MGT⁃CCHP [J]. Journal of Southeast University （Natural Science Edition） , 2017 , 47 （ 3 ）: 500 ⁃ 505 . （in Chinese）

COOK J , POWELL B . Modeling of an internal combustion engine for control analysis [J]. IEEE Control Systems Magazine , 1988 , 8 （ 4 ）: 20 ⁃ 26 .

乔宗良 , 张蕾 , 周建新 , 等 . 一种改进的CPSO⁃LSSVM软测量模型及其应用 [J]. 仪器仪表学报 , 2014 , 35 （ 1 ）: 234 ⁃ 240 .

QIAO Zongliang , ZHANG Lei , ZHOU Jianxin , et al . Soft sensor modeling method based on improved CPSO⁃LSSVM and its applications [J]. Chinese Journal of Scientific Instrument , 2014 , 35 （ 1 ）: 234 ⁃ 240 . （in Chinese）

PEREZ J , RIBEIRO B , PEREZ C . Mahalanobis distance metric learning algorithm for instance⁃based data stream classification [C]∥ Proceedings of 2016 International Joint Conference on Neural Networks . Vancouver : IEEE , 2016 : 1857 ⁃ 1862 .

张焱 , 汤宝平 , 熊鹏 . 多尺度变异粒子群优化MK⁃LSSVM的轴承寿命预测 [J]. 仪器仪表学报 , 2016 , 37 （ 11 ）: 2489 ⁃ 2496 .

ZHANG Yan , TANG Baoping , XIONG Peng . Rolling element bearing life prediction based on multi⁃scale mutation particle swarm optimized multi⁃kernel least square support vector machine [J]. Chinese Journal of Scientific Instrument , 2016 , 37 （ 11 ）: 2489 ⁃ 2496 . （in Chinese）

COELHO L S , HERRERA B M . Fuzzy identification based on a chaotic particle swarm optimization approach applied to a nonlinear yo⁃yo motion system [J]. IEEE Transactions on Industrial Electronics , 2007 , 54 （ 6 ）: 3234 ⁃ 3245 .

COELHO L S , MARIANI V C . A novel chaotic particle swarm optimization approach using Hénon map and implicit filtering local search for economic load dispatch [J]. Chaos,Solitons and Fractals , 2009 , 39 （ 2 ）: 510 ⁃ 518 .

ZHU Y , ÖZGÜNER Ü . Constrained model predictive control for nonholonomic vehicle regulation problem [J]. IFAC Proceedings Volumes , 2008 , 41 （ 2 ）: 9552 ⁃ 9557 .

赵家豪 , 魏民祥 , 丁玉章 , 等 . 增程式APU混沌退火混合粒子群优化模糊PID动态控制 [J]. 航空动力学报 , 2021 , 36 （ 6 ）: 1213 ⁃ 1221 .

ZHAO Jiahao , WEI Minxiang , DING Yuzhang , et al . Dynamic control strategy of extended⁃range APU based on fuzzy PID optimized by CAHPSO [J]. Journal of Aerospace Power , 2021 , 36 （ 6 ）: 1213 ⁃ 1221 . （in Chinese）

GONG C , HU Y , GAO J , et al . An improved delay⁃suppressed sliding⁃mode observer for sensorless vector⁃controlled PMSM [J]. IEEE Transactions on Industrial Electronics , 2020 , 67 （ 7 ）: 5913 ⁃ 5923 .

REN G , MA G . A novel scheme design of power unit for extended range electric vehicles [J]. International Journal of Electric and Hybrid Vehicles , 2012 , 4 （ 4 ）: 314 ⁃ 326 .

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