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author:

Li, C. (Li, C..) [1] | Zhang, H. (Zhang, H..) [2] (Scholars:张和洪) | Xiao, G. (Xiao, G..) [3] | Zhai, C. (Zhai, C..) [4] | Dan, Z. (Dan, Z..) [5] | Wang, X. (Wang, X..) [6]

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Scopus

Abstract:

The flight environment simulation system plays a crucial role in aeroengine testing, replicating real mission pressure and temperature conditions. However, existing systems face challenges in handling strong measurement noises and total disturbances during transient tests, leading to inaccurate simulations and potential actuator damage. To address these gaps, an enhanced tracking differentiator based active disturbance rejection control scheme is proposed and implemented. Our method introduces two key innovations: a discrete-time optimal control law that dynamically adjusts control inputs based on state transition and sampling times, and a phase-advancing method that mitigates filtering phase delays by incorporating derivative signals to predict input trends. These components are integrated into a novel tracking differentiator, enhancing the estimation capability of the extended state observer in active disturbance rejection control. Frequency-domain analysis demonstrates the proposed tracking differentiator's superior filtering performance and phase quality. Simulations of intake environment pressure during aeroengine transient tests reveal that, compared to traditional tracking differentiator-based active disturbance rejection control, the proposed approach significantly reduces both control signal oscillations and setpoint deviations by 75.44% and 53.9%, respectively. These improvements effectively address environment simulation deviations and unnecessary actuator wear, thereby enhancing the accuracy and reliability of aeroengine testing. © 2024 Elsevier Masson SAS

Keyword:

Active disturbance rejection control Aeroengine transient tests Filtering Flight environment simulation system Intake pressure simulation Phase delay Time criterion Tracking differentiator

Community:

  • [ 1 ] [Li C.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Li C.]Advanced Technology Innovation Institute, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Zhang H.]College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Zhang H.]Advanced Technology Innovation Institute, Fuzhou University, Fuzhou, 350108, China
  • [ 5 ] [Zhang H.]Key Laboratory of Intelligent Metro of Universities in Fujian, Fuzhou, 350108, China
  • [ 6 ] [Xiao G.]School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore
  • [ 7 ] [Zhai C.]School of Automation, China University of Geosciences, Wuhan, 430074, China
  • [ 8 ] [Dan Z.]Sichuan Gas Turbine Research Institute, Aero Engine Corporation of China, Mianyang, 621300, China
  • [ 9 ] [Wang X.]Sichuan Gas Turbine Research Institute, Aero Engine Corporation of China, Mianyang, 621300, China

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Source :

Aerospace Science and Technology

ISSN: 1270-9638

Year: 2024

Volume: 155

5 . 0 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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