IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v288y2024ics0360544223033285.html
   My bibliography  Save this article

Design and implementation for the state time-delay and input saturation compensator of gas turbine aero-engine control system

Author

Listed:
  • Liu, Xiaofeng
  • Song, Enshu
  • Zhang, Liming
  • Luan, Yongjun
  • Wang, Jianhua
  • Luo, Chenshuang
  • Xiong, Liuqi
  • Pan, Qiang

Abstract

In order to obtain desired steady-state and transient performance of a gas turbine aero-engine during its operation, a usual way is to control the engine to operate in a manner close to its physical limits. The thermodynamic performance of a gas turbine aero-engine varies greatly within a wide working envelope, affected by factors such as engine performance degradation, actuator response lag and combustion time-delay. When the engine works in extreme conditions, for example rapid acceleration, some phenomena such as over-speed, over-temperature and over-pressure may occur. For this reason, various restrictions are often set in the engine control system to ensure safety during its operation, which are often realized by the form of saturation. In this paper, a compensation structure for gas turbine aero-engine state time-delay and input saturation is proposed. At first, the problems frequently occurred in the gas turbine aero-engine control system are investigated. And the gas turbine aero-engine control model is derived based on a thermodynamic non-linear model and its linearization model is established, together with its designed compensation structure. Differing from the existing technologies, a combination of dynamic system input saturation feedback and static state time-delay feedback is adopted in the proposed model. Then, the saturated nonlinearity and time-delay characteristic are introduced as convex combinations in the stability analysis. The local stability conditions of the closed-loop system are obtained by using Lyapunov–Krasovskii functionals and linear matrix inequalities (LMIs). Finally, hardware-in-loop (HIL) experiments are conducted to verify the feasibility of the proposed compensation method.

Suggested Citation

  • Liu, Xiaofeng & Song, Enshu & Zhang, Liming & Luan, Yongjun & Wang, Jianhua & Luo, Chenshuang & Xiong, Liuqi & Pan, Qiang, 2024. "Design and implementation for the state time-delay and input saturation compensator of gas turbine aero-engine control system," Energy, Elsevier, vol. 288(C).
  • Handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223033285
    DOI: 10.1016/j.energy.2023.129934
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223033285
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.129934?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xu, Maojun & Liu, Jinxin & Li, Ming & Geng, Jia & Wu, Yun & Song, Zhiping, 2022. "Improved hybrid modeling method with input and output self-tuning for gas turbine engine," Energy, Elsevier, vol. 238(PA).
    2. Wei, Zhiyuan & Zhang, Shuguang & Jafari, Soheil & Nikolaidis, Theoklis, 2022. "Self-enhancing model-based control for active transient protection and thrust response improvement of gas turbine aero-engines," Energy, Elsevier, vol. 242(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Xinhai & Wang, Kang & Geng, Jia & Li, Ming & Song, Zhiping, 2024. "A fault-tolerant acceleration control strategy for turbofan engine based on multi-layer perceptron with exponential Gumbel loss," Energy, Elsevier, vol. 294(C).
    2. Feng, Hailong & Liu, Bei & Xu, Maojun & Li, Ming & Song, Zhiping, 2024. "Model-based deduction learning control: A novel method for optimizing gas turbine engine afterburner transient," Energy, Elsevier, vol. 292(C).
    3. Zheng, Qiangang & Zhang, Hongwei & Hu, Chenxu & Zhang, Haibo, 2024. "Performance seeking control method for minimum pollutant emission mode for turbofan engine," Energy, Elsevier, vol. 289(C).
    4. Sharifi, Alireza & Salarieh, Hassan, 2023. "An adaptive synergetic controller applied to heavy-duty gas turbine unit," Applied Energy, Elsevier, vol. 333(C).
    5. Huang, Yufeng & Tao, Jun & Zhao, Junyi & Sun, Gang & Yin, Kai & Zhai, Junyi, 2023. "Graph structure embedded with physical constraints-based information fusion network for interpretable fault diagnosis of aero-engine," Energy, Elsevier, vol. 283(C).
    6. Liao, Zengbu & Zhan, Keyi & Zhao, Hang & Deng, Yuntao & Geng, Jia & Chen, Xuefeng & Song, Zhiping, 2024. "Addressing class-imbalanced learning in real-time aero-engine gas-path fault diagnosis via feature filtering and mapping," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    7. Yu, Jianxi & Petersen, Nils & Liu, Pei & Li, Zheng & Wirsum, Manfred, 2022. "Hybrid modelling and simulation of thermal systems of in-service power plants for digital twin development," Energy, Elsevier, vol. 260(C).
    8. Huang, Yufeng & Tao, Jun & Sun, Gang & Wu, Tengyun & Yu, Liling & Zhao, Xinbin, 2023. "A novel digital twin approach based on deep multimodal information fusion for aero-engine fault diagnosis," Energy, Elsevier, vol. 270(C).
    9. Zhao, Hang & Liao, Zengbu & Liu, Jinxin & Li, Ming & Liu, Wei & Wang, Lei & Song, Zhiping, 2022. "A highly robust thrust estimation method with dissimilar redundancy framework for gas turbine engine," Energy, Elsevier, vol. 245(C).
    10. Chen, Yu-Zhi & Tsoutsanis, Elias & Wang, Chen & Gou, Lin-Feng, 2023. "A time-series turbofan engine successive fault diagnosis under both steady-state and dynamic conditions," Energy, Elsevier, vol. 263(PD).
    11. Jia, Xingyun & Zhou, Dengji, 2024. "Multi-variable anti-disturbance controller with state-dependent switching law for adaptive cycle engine," Energy, Elsevier, vol. 288(C).
    12. Dao, Fang & Zeng, Yun & Qian, Jing, 2024. "Fault diagnosis of hydro-turbine via the incorporation of bayesian algorithm optimized CNN-LSTM neural network," Energy, Elsevier, vol. 290(C).
    13. Wang, Pengfei & Zhu, Ze & Liang, Wenlong & Liao, Longtao & Wan, Jiashuang, 2023. "Hybrid mechanistic and neural network modeling of nuclear reactors," Energy, Elsevier, vol. 282(C).
    14. Song, Jie & Wang, Yong & Ji, Chuang & Zhang, Haibo, 2024. "Real-time optimization control of variable rotor speed based on Helicopter/ turboshaft engine on-board composite system," Energy, Elsevier, vol. 301(C).
    15. Cai, Changpeng & Wang, Yong & Fang, Juan & Chen, Haoying & Zheng, Qiangang & Zhang, Haibo, 2023. "Multiple aspects to flight mission performances improvement of commercial turbofan engine via variable geometry adjustment," Energy, Elsevier, vol. 263(PA).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223033285. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.