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Adaptive dynamic programming for ramjet intelligent tracking control via neural network-enhanced equilibrium manifold expansion estimator

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  • Lv, Chengkun
  • Lan, Zhu
  • Chang, Juntao
  • Yu, Daren

Abstract

Precise control of the operational state of turbine-based combined cycle (TBCC) high-speed channel is a crucial factor in ensuring the reliable implementation of the mode transition (MT). To achieve this goal, offline training and online updating of the control-oriented model (COM), neural network (NN), and reinforcement learning are considered in this study. First, the Mach number (Ma) is introduced into the NN-enhanced equilibrium manifold expansion (NNEME) model to characterize the wide-speed-range operational characteristics of the ramjet engine. Furthermore, the extended state observer (ESO) is employed to further estimate unmodelled dynamics, and the adaptive dynamic programming (ADP) error controller is established to address the control problem of the ramjet engine during MT process. Throughout the entire MT process, the error confidence intervals for π40 and π32 output by the NNEME model are reduced by 92.97 % and 93.66 %, respectively. Moreover, hardware-in-the-loop (HIL) results indicate that the ESO + NNEME ADP control system is more stable and reduces state overshoots by up to 56.9178 % and 82.8062 %, respectively. The proposed advanced control system composed of ESO + NNEME steady-state controller and ADP error controller exhibits a better control performance and robustness within the entire MT process.

Suggested Citation

  • Lv, Chengkun & Lan, Zhu & Chang, Juntao & Yu, Daren, 2024. "Adaptive dynamic programming for ramjet intelligent tracking control via neural network-enhanced equilibrium manifold expansion estimator," Energy, Elsevier, vol. 309(C).
    • Handle: RePEc:eee:energy:v:309:y:2024:i:c:s0360544224028706
    DOI: 10.1016/j.energy.2024.133095
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    References listed on IDEAS

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    1. Lv, Chengkun & Xu, Haiqi & Chang, Juntao & Wang, Youyin & Chen, Ruoyu & Yu, Daren, 2022. "Mode transition analysis of a turbine-based combined-cycle considering ammonia injection pre-compressor cooling and variable-geometry ram-combustor," Energy, Elsevier, vol. 261(PB).
    2. Wang, Youyin & Hou, Wenxin & Zhang, Junlong & Tang, Jingfeng & Chang, Juntao & Bao, Wen, 2021. "Research on the operating boundary of the dual mode scramjet with a constant area combustor through thermodynamic cycle analysis," Energy, Elsevier, vol. 216(C).
    3. Lin, Zhiyi & Song, Chunyue & Zhao, Jun & Yin, Huan, 2022. "Improved approximate dynamic programming for real-time economic dispatch of integrated microgrids," Energy, Elsevier, vol. 255(C).
    4. Lv, Chengkun & Huang, Qian & Wang, Ziao & Chang, Juntao & Yu, Daren, 2024. "Mode transition control law analysis of ammonia MIPCC aeroengine considering inlet–compressor safety matching," Energy, Elsevier, vol. 288(C).
    5. Kim, Sangjo & Kim, Kuisoon & Son, Changmin, 2020. "Transient system simulation for an aircraft engine using a data-driven model," Energy, Elsevier, vol. 196(C).
    6. Cui, Zhiquan & Yan, Zhiqi & Zhao, Minghang & Zhong, Shisheng, 2022. "Gas path parameter prediction of aero-engine based on an autoregressive discrete convolution sum process neural network," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    7. Kong, Yan & Xu, Nan & Liu, Qiao & Sui, Yan & Yue, Fenglai, 2023. "A data-driven energy management method for parallel PHEVs based on action dependent heuristic dynamic programming (ADHDP) model," Energy, Elsevier, vol. 265(C).
    8. Lv, Chengkun & Lan, Zhu & Wang, Ziao & Chang, Juntao & Yu, Daren, 2024. "Intelligent ammonia precooling control for TBCC mode transition based on neural network improved equilibrium manifold expansion model," Energy, Elsevier, vol. 288(C).
    Full references (including those not matched with items on IDEAS)

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