Articles

Re-entry robust fault tolerant attitude control for RLVs considering unknown disturbances

  • Wu LIU ,
  • Yunyan WU ,
  • Wei LIU ,
  • Mingming TIAN ,
  • Tianpeng HUANG
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  • AVIC Xi’an Flight Automatic Control Research Institute,Xi’an 710000,China
E-mail: liuwu@nuaa.edu.cn

Received date: 2022-06-01

  Revised date: 2022-07-11

  Accepted date: 2022-08-09

  Online published: 2022-08-17

Abstract

Aiming at the attitude control problem of reusable launch vehicle in complex re-entry environment, and considering the unknown disturbance of atmosphere, the uncertainty of aerodynamic parameter modeling and the possible partial faults of actuator, the controllers of attitude angle loop and angular velocity loop are designed based on incremental backstepping and Radial Basis Function (REF) neural network. Because the neural network has good unknown approximation ability, RBF neural network is used to estimate the high-order term of Taylor expansion and the influence of the above unknown disturbances in the incremental backstepping design process, and compensate them in the control law. The simulation results show that the designed control system can effectively improve the tracking accuracy of instructions under the influence of unknown disturbances, and has less dependence on the modeling of aircraft information, so it has good robust fault tolerance.

Cite this article

Wu LIU , Yunyan WU , Wei LIU , Mingming TIAN , Tianpeng HUANG . Re-entry robust fault tolerant attitude control for RLVs considering unknown disturbances[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(S1) : 727787 -727787 . DOI: 10.7527/S1000-6893.2022.27787

References

1 LIU J J, SUN M W, CHEN Z Q, et al. Output feedback control for aircraft at high angle of attack based upon fixed-time extended state observer[J]. Aerospace Science and Technology201995: 105468.
2 林海兵, 都延丽, 刘武, 等. 基于FTDO的RLV再入段鲁棒容错姿态控制[J]. 电光与控制202027(3): 46-51.
  LIN H B, DU Y L, LIU W, et al. Robust fault-tolerant attitude control for the RLV during reentry based on fixed-time disturbance observer[J]. Electronics Optics & Control202027(3): 46-51 (in Chinese).
3 DONG Q, ZONG Q, TIAN B L, et al. Adaptive disturbance observer-based finite-time continuous fault-tolerant control for reentry RLV[J]. International Journal of Robust and Nonlinear Control201727(18): 4275-4295.
4 LIANG X H, WANG Q, HU C H, et al. Fixed-time observer based fault tolerant attitude control for reusable launch vehicle with actuator faults[J]. Aerospace Science and Technology2020107: 106314.
5 LI P, YU X, XIAO B. Adaptive quasi-optimal higher order sliding-mode control without gain overestimation[J]. IEEE Transactions on Industrial Informatics201814(9): 3881-3891.
6 ZHANG L, WEI C Z, WU R,et al. Adaptive fault-tolerant control for a VTVL reusable launch vehicle[J]. Acta Astronautica2019159: 362-370.
7 陈佳晔, 白瑜亮, 穆荣军, 等. 基于自适应滑模的重复使用运载器容错控制[J]. 中国惯性技术学报201927(2): 255-259.
  CHEN J Y, BAI Y L, MU R J, et al. Fault-tolerant control of RLV based on adaptive sliding mode theory[J]. Journal of Chinese Inertial Technology201927(2): 255-259 (in Chinese).
8 ZHANG Y, LI A J, HUANG B, et al. Sliding-mode based adaptive fault tolerant control for re-entry reusable launch vehicle[C]∥ 2017 International Conference on Mechanical, System and Control Engineering. Piscataway: IEEE Press, 2017: 220-224.
9 ZHANG R D, TAO J L. A nonlinear fuzzy neural network modeling approach using an improved genetic algorithm[J]. IEEE Transactions on Industrial Electronics201865(7): 5882-5892.
10 XIA R S, CHEN M, WU Q X,et al. Neural network based integral sliding mode optimal flight control of near space hypersonic vehicle[J]. Neurocomputing2020379: 41-52.
11 窦立谦, 毛奇, 苏沛华. 基于自适应模糊H控制的可重复使用运载器再入姿态控制[J]. 控制与决策201833(7): 1181-1189.
  DOU L Q, MAO Q, SU P H. Adaptive fuzzy H attitude control design for reentry RLV[J]. Control and Decision201833(7): 1181-1189 (in Chinese).
12 MAO Q, DOU L Q, ZONG Q, et al. Attitude controller design for reusable launch vehicles during reentry phase via compound adaptive fuzzy H-infinity control[J]. Aerospace Science and Technology201872: 36-48.
13 XUE Q, DUAN H B. Robust attitude control for reusable launch vehicles based on fractional calculus and pigeon-inspired optimization[J]. IEEE/CAA Journal of Automatica Sinica20174(1): 89-97.
14 吴雨珊, 江驹, 甄子洋, 等. 基于回馈递推的可变翼高超声速飞行器智能非线性控制[J]. 哈尔滨工程大学学报201637(7): 963-968.
  WU Y S, JIANG J, ZHEN Z Y, et al. Intelligent nonlinear control for the hypersonic morphing vehicle based on the backstepping method[J]. Journal of Harbin Engineering University201637(7): 963-968 (in Chinese).
15 徐文萤, 江驹, 甄子洋, 等. 基于Back-Stepping鲁棒自适应动态面的近空间飞行器控制[J]. 电光与控制201825(11): 15-20.
  XU W Y, JIANG J, ZHEN Z Y, et al. Near space vehicle control based on Back-Stepping robust adaptive dynamic surface[J]. Electronics Optics & Control201825(11): 15-20 (in Chinese).
16 PAUL A B, VAN KAMPEN E J, CHU Q P. Incremental backstepping for robust nonlinear flight control[C]∥Proceeding of EuroGNC 2013, 2nd CEAS Specialist Conference on Guidance, Navigation & Control. Brussels: CEAS, 2013: 1444-1463.
17 WANG X R, VAN KAMPEN E J. Incremental backstepping sliding mode fault-tolerant flight control: AIAA-2019-0110[R]. Reston: AIAA, 2019.
18 LU P, VAN KAMPEN E J. Active fault-tolerant control system using incremental backstepping approach AIAA-2015-1312[R]. Reston: AIAA, 2015.
19 刘武, 都延丽, 林海兵, 等. 基于改进增量反演法的RLV鲁棒容错控制[J]. 电光与控制202128(6): 11-15.
  LIU W, DU Y L, LIN H B, et al. Robust fault-tolerant control of RLVs based on improved incremental backstepping[J]. Electronics Optics & Control202128(6): 11-15 (in Chinese).
20 MOOIJ E, MEASE K, BENITO J. Robust re-entry guidance and control system design and analysis: AIAA-2007-6779[R]. Reston: AIAA, 2007.
21 张鹏. 可重复使用运载器再入预测校正制导与控制系统设计[D]. 南京: 南京航空航天大学, 2018: 17-21.
  ZHANG P. Research on predictive correction entry guidance and control system for reusable launch vehicle[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2018: 17-21 (in Chinese).
22 PARK J, SANDBERG I W. Universal approximation using radial-basis-function networks[J]. Neural Computation19913(2): 246-257.
23 冯福沁, 张胜修, 曹立佳, 等. 基于RBF神经网络的自适应反演大机动飞行控制器设计[J]. 电光与控制201320(5): 63-68.
  FENG F Q, ZHANG S X, CAO L J, et al. Design of adaptive backstepping controller for high maneuvering flight based on RBF neural network[J]. Electronics Optics & Control201320(5): 63-68 (in Chinese).
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