Finite-time state-constrained adaptive fault-tolerant control for heavy launch vehicles with input quantization

Ruitao Zhang, Zheng Wang, Yangwang Fang, Hang Guo, Wenxing Fu, Jie Yan, Lulu Rong

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes the finite-time state-constrained adaptive fault-tolerant control method for a class of heavy launch vehicles subject to quantized input signals and actuator faults. Firstly, the attitude dynamic model of the heavy launch vehicles suffering from the actuator faults and disturbances is formulated. Secondly, to deal with the completely unknown nonlinear functions, radial basis function neural networks (RBFNNs) are introduced for approximation and compensation. Meanwhile, the barrier Lyapunov function (BLF) is introduced to ensure that all the states in the closed-loop system are bounded and the constraints of the system states are satisfied. As a result, the finite-time state-constrained adaptive fault-tolerant control structure is constructed for the heavy launch vehicles and the semi-globally practical finite-time stability (SGPFS) of the closed-loop control system is proved. Finally, numerical simulation results show the effectiveness and the satisfactory performance of the proposed control algorithm.

Original languageEnglish
Pages (from-to)745-763
Number of pages19
JournalProceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
Volume238
Issue number8
DOIs
StatePublished - Jun 2024

Keywords

  • fault-tolerant control
  • finite-time
  • heavy launch vehicles
  • Neural network
  • state constraints

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