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Adaptive fixed-time quantized fault-tolerant attitude control for hypersonic reentry vehicle

  • Harbin Institute of Technology Weihai

Research output: Contribution to journalArticlepeer-review

Abstract

This paper focuses on the adaptive fixed-time quantized fault-tolerant attitude tracking problem for hypersonic reentry vehicle (HRV). Due to the strong nonlinearity, tight coupling, uncertain characteristics and potential actuator faults, the attitude control of HRV poses a considerable challenge. By resorting to feedback linearization technique, the inherently nonlinear attitude model of HRV is decoupled into a linear control-oriented model, where the actuator malfunction, quantization nonlinearities and multiple disturbances are incorporated into the lumped disturbance. Then a fixed-time neural network disturbance observer is designed to estimate the lumped disturbance, with the practical fixed-time stability of the observation error ensured independent of initial conditions. Subsequently, by using a hyperbolic-tangent-like function, a novel paradigm is proposed for achieving adaptive fixed-time convergence and based on the paradigm, an adaptive fixed-time nonsingular sliding mode controller is proposed. The main features of the controller include: 1) The controller gain is adjusted adaptively following the current magnitude of the output variable to obtain high transient performance. 2) The tracking error can converge to zero within a fixed time even in the case of actuator faults and signal quantization. 3) A hysteretic quantizer is implemented in the attitude control loop such that the on-board communication load can be significantly reduced. Moreover, the proposed fault-tolerant control scheme design is non-recursive, rendering the controller structure simple. Ultimately, the effectiveness of the proposed method is demonstrated by numerical simulations.

Original languageEnglish
Pages (from-to)386-399
Number of pages14
JournalNeurocomputing
Volume520
DOIs
StatePublished - 1 Feb 2023

Keywords

  • Adaptive sliding mode control
  • Fault-tolerant attitude control
  • Fixed-time neural network observer
  • Hypersonic reentry vehicle
  • Quantization

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