Electrical Engineering

Liben Yang 1, Wenjun Wei1, Jianfeng Yang1, and Dong Wang2

1School of Automation Electrical Engineering , Lanzhou Jiaotong University, Lanzhou,Gansu 710070, China
2510 Research Institute of the Fifth Research Institute of China Aerospace Science and Technology Group, Lanzhou,Gansu 730000, China

 

Received: September 14, 2022
Accepted: December 16, 2022
Publication Date: January 4, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202310_26(10).0004  


The tilt rotor aircraft is capable of both low-speed hovering and high-speed flight, which has a larger flight envelope. However, during its transition phase, due to the change of the mechanical structure, the dynamic characteristics of the rotor and the aerodynamic characteristics of the fixed wing have intercoupling, which present strong nonlinear characteristics and weak anti-disturbance ability. To address this problem, this paper proposes an anti-wind disturbance decoupling control algorithm based on the improved active disturbance rejection control (ADRC) for the transition phase of the tilt rotor aircraft, and presents an improved particle swarm optimization (PSO) algorithm to optimize the parameters of the control system in the transition phase. According to the simulation results, our algorithm can provide better anti-disturbance ability than the traditional algorithm, realize decoupling control between different states, and effectively improve the flight safety in the transition phase.


Keywords: Tiltrotor aircraft; Transition stage; Wind disturbance estimation; Transition corridor; Decoupling control


  1. [1] Z. Liu, D. Theilliol, Y. He, F. Gu, L. Yang, and J. Han, (2021) “Active model-based nonlinear system identification of quad tilt-rotor UAV with flight experiments" Science China Information Sciences: DOI: 10.7641/CTA.2021.00346.
  2. [2] W. Zhigang, Z. Hong, D. Dengyan, J. Yuanyang, and L. Jianbo, (2020) “Application of improved active disturbance rejection control algorithm in tilt quad rotor"Chinese Journal of Aeronautics 33(6): 1625–1641. DOI: 10.1016/j.cja.2020.01.002.
  3. [3] G.Wen, D.Wu, H. Yin, and D. Zhang, (2020) “Coupled CFD/MBD Method for a Tilt Tri-rotor UAV in Conversion of Flight Modes" International Journal of Computational Fluid Dynamics 34(5): 363–379. DOI: 10.1080/10618562.2020.1778169.
  4. [4] A. Prach and E. Kayacan, (2018) “An MPC-based position controller for a tilt-rotor tricopter VTOL UAV" Optimal control applications and methods 39(1): 343–356. DOI: 10.1002/oca.2350.
  5. [5] B. X. Dong.Wang, (2020) “Adaptive robust fault tolerant control of the tilt tri-rotor unmanned aerial vehicle" Control Theory Applications 37(4): 784–792. DOI: 10.7641/CTA.2019.90172.
  6. [6] R. Fu, H. Sun, and J. Zeng, (2019) “Exponential stabilisation of nonlinear parameter-varying systems with applications to conversion flight control of a tilt rotor aircraft" International Journal of Control 92(11): 2473–2483. DOI: 10.1080/00207179.2018.1442022.
  7. [7] N. El Gmili, M. Mjahed, A. El Kari, and H. Ayad, (2020) “Particle swarm optimization based proportional derivative parameters for unmanned tilt-rotor flight control and trajectory tracking" Automatika 61(2): 189–206. DOI: 10.1080/00051144.2019.1698191.
  8. [8] B. Xian and W. Hao, (2018) “Nonlinear robust faulttolerant control of the tilt trirotor UAV under rear servo’s stuck fault: Theory and experiments" IEEE Transactions on Industrial Informatics 15(4): 2158–2166. DOI: 10.1109/TII.2018.2858143.
  9. [9] K. Lu, Z. Yang, Q. Zhang, C. Xu, H. Xu, and X. Xu, (2020) “Active disturbance rejection flight control method for thrust-vectored quadrotor with tiltable rotors" Control Theory & Applications 37(6): 1377–1387. DOI: 10.7641/CTA.2019.90305.
  10. [10] N. T. Hegde, V. George, C. G. Nayak, and K. Kumar, (2020) “Transition flight modeling and robust control of a VTOL unmanned quad tilt-rotor aerial vehicle" Indonesian Journal of Electrical Engineering and Computer Science 18(3): 1252–1261. DOI: 10.11591/ijeecs.v18.i3.
  11. [11] Y. Xufei and C. Renliang, (2019) “Augmented flight dynamics model for pilot workload evaluation in tilt-rotor aircraft optimal landing procedure after one engine failure" Chinese Journal of Aeronautics 32(1): 92–103. DOI: 10.1016/j.cja.2018.06.010.
  12. [12] A. Houari, I. Bachir, D. K. Mohamed, and M. Kara- Mohamed, (2020) “PID vs LQR controller for tilt rotor airplane" International Journal of Electrical and Computer Engineering (IJECE) 10(6): 6309–6318. DOI: 10.11591/ijece.v10i6.pp6309-6318.
  13. [13] M. Hassanalian, R. Salazar, and A. Abdelkefi, (2019) “Conceptual design and optimization of a tilt-rotor micro air vehicle" Chinese Journal of Aeronautics 32(2): 369–381. DOI: 10.1016/j.cja.2018.10.006.
  14. [14] N. T. Hegde, V. George, C. G. Nayak, and K. Kumar, (2019) “Design, dynamic modelling and control of tilt-rotor UAVs: a review" International Journal of Intelligent Unmanned Systems 8(3): 143–161. DOI: 10.1108/IJIUS-01-2019-0001.
  15. [15] Q.-Y. Xia, J.-F. Xu, and L. Zhang, (2013) “Model-free adaptive attitude controller for a tilt-rotor aircraft" Systems Engineering and Electronics 35(1): 146–151. DOI: 10.3969/j.issn.1001-506X.2013.01.24.
  16. [16] Z. Wang, J. Li, and D. Duan, (2020) “Manipulation strategy of tilt quad rotor based on active disturbance rejection control" Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 234(3): 573–584. DOI: 10.1177/0954410019875534.
  17. [17] Y. Cao, Q. Zhao, Y. Ye, and Y. Xiong, (2019) “ADRCbased current control for grid-tied inverters: Design, analysis, and verification" IEEE Transactions on Industrial Electronics 67(10): 8428–8437. DOI: 10.1109/TIE.2019.2949513.
  18. [18] T. He, Z. Wu, D. Li, and J. Wang, (2019) “A tuning method of active disturbance rejection control for a class of high-order processes" IEEE Transactions on Industrial Electronics 67(4): 3191–3201. DOI: 10.1109/TIE.2019.2908592.
  19. [19] Z. Li, Y. Wei, X. Zhou, J. Wang, J. Wang, and Y. Wang, (2020) “Differential flatness-based ADRC scheme for underactuated fractional-order systems" International Journal of Robust and Nonlinear Control 30(7):2832–2849. DOI: 10.1002/rnc.4905.
  20. [20] Y. Qu, Z. Xing, D. Yuan, and Y. Zhang, (2016) “Wind field estimation based on position and attitude information of quadrotor in hover" Journal of Northwestern Polytechnical University 34(4): 684–690. DOI: 10.3969/j.issn.1000-2758.2016.04.020.

Latest Articles

Multi-level Semantic Fusion Network for Few-shot Multimedia Image Recognition in Education Management
Multi-level Semantic Fusion Network for Few-shot Multimedia Image Recognition in Education ManagementVolume 28, Issue 2 (In Press)

Read more: ...

River bank erosion prediction using multivariable linear regression
River bank erosion prediction using multivariable linear regressionVolume 27, Issue 12 (In Press)

Read more: ...

Optimization of Ultrasound-Assisted Pectin Extraction from Durian Rind
Optimization of Ultrasound-Assisted Pectin Extraction from Durian RindVolume 28, Issue 2 (In Press)

Read more: ...

Short-time prediction model for cross-section passenger flow in urban transit trains using GCN-AM-BiLSTM
Short-time prediction model for cross-section passenger flow in urban transit trains using GCN-AM-BiLSTMVolume 28, Issue 2 (In Press)

Read more: ...

Response Prediction Analysis of RC Frame Structures Using Support Vector Machine Algorithm
Response Prediction Analysis of RC Frame Structures Using Support Vector Machine AlgorithmVolume 28, Issue 2 (In Press)

Read more: ...

Using the non-dominated sorting genetic algorithm II for multi-objective optimization of acoustic performance in sandwich panels with cellular honeycomb core
Using the non-dominated sorting genetic algorithm II for multi-objective optimization of acoustic performance in sandwich panels with cellular honeycomb coreVolume 28, Issue 2 (In Press)

Read more: ...

Analyzing Glass Configurations For Energy Efficiency In Building Envelopes: A Comparative
Analyzing Glass Configurations For Energy Efficiency In Building Envelopes: A ComparativeVolume 28, Issue 2 (In Press)

Read more: ...

Assessment of the optimal gold recovery rate through heap leach extraction process from hydrothermal alteration zone ore
Assessment of the optimal gold recovery rate through heap leach extraction process from hydrothermal alteration zone oreVolume 28, Issue 2 (In Press)

Read more: ...

Research on the Time-Varying Relationship between Macroeconomic Variables and the Stock Market Volatility Based on TVP-VAR Model
Research on the Time-Varying Relationship between Macroeconomic Variables and the Stock Market Volatility Based on TVP-VAR ModelVolume 28, Issue 2 (In Press)

Read more: ...