Adaptive fault tolerant control for hypersonic flight vehicle system with state constraints

Peng, Zhiyu; Qi, Ruiyun; Jiang, Bin

doi:10.1016/j.jfranklin.2020.07.014

Cited by 19 publications

(17 citation statements)

References 32 publications

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“…Remark Previous BLF‐based HFV control studies 30,32,33,35,38,40 constructed the BLF only based on the tracking error

e_{2}

and its bounds, whereas in this study, the AIBLF

L_{b 2}

is designed directly based on the bounds of

x_{2}

. Compared with existed studies, there is no need to give the bounds of

e_{2}

and

x_{2 c}

separately, so that the constraint setting is simplified.…”

Section: Controller Designmentioning

confidence: 99%

“…Due to the effect on limiting the designated states or outputs, the BLF is an effective tool for state‐constrained problems 26‐29 . In References 30‐32, the BLF is utilized in the HFV control, where the tracking errors of the relative states are restricted. Considering the asymmetric constraint on AOA, the asymmetric BLF is utilized in Reference 33, while in Reference 34, the asymmetric time‐varying error bounds is guaranteed using an tan‐type BLF.…”

Section: Introductionmentioning

confidence: 99%

“…It should be noticed that in References 30, 32, 33, 35, 38, and 40 and many similar studies, the controller mostly can only prove the constraint on the tracking error, while the state constraint is guaranteed by additionally restrict the command signal in a different interval. To be specific, if the state x is to be constrained while its tracking error

e_{x} = x - x_{d}

, the existed methods achieve the constraint in two steps: (1) setting

x_{d}^{l} < x_{d} < x_{d}^{u}

, and (2) designing the PPC or BLF‐based controller to satisfy

e^{l} < e < e^{u}

.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Asymmetric integral BLF based state‐constrained flight control using NN and DOB

Guo

Yan

et al. 2022

Intl J Robust & Nonlinear

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This article proposes an adaptive back‐stepping flight controller under angle of attack (AOA) constraints. Taking the hypersonic flight vehicle (HFV) for example, considering the AOA constraints caused by the scramjet intake requirements, the asymmetric integral barrier Lyapunov function is used to design the controller, while the AOA is directly limited to a predefined interval without setting the tracking error and virtual control constraints separately. Furthermore, the neural networks and disturbance observer are applied in the controller to deal with the model uncertainty and external disturbance. The system stability and the AOA constraints are proved via Lyapunov analysis. Simulation tests on HFV longitudinal dynamics present that the proposed controller can prevent the AOA from exceeding the given bounds while altitude and velocity tracking.

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“…Remark Previous BLF‐based HFV control studies 30,32,33,35,38,40 constructed the BLF only based on the tracking error

e_{2}

and its bounds, whereas in this study, the AIBLF

L_{b 2}

is designed directly based on the bounds of

x_{2}

. Compared with existed studies, there is no need to give the bounds of

e_{2}

and

x_{2 c}

separately, so that the constraint setting is simplified.…”

Section: Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

e_{x} = x - x_{d}

, the existed methods achieve the constraint in two steps: (1) setting

x_{d}^{l} < x_{d} < x_{d}^{u}

, and (2) designing the PPC or BLF‐based controller to satisfy

e^{l} < e < e^{u}

.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Asymmetric integral BLF based state‐constrained flight control using NN and DOB

Guo

Yan

et al. 2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…All these controllers have been applied to the longitudinal mode of an HFV. An analogous method has been employed in [189], where the designed controller has been applied to an HFV considering flexible dynamics and state constraints.…”

Section: Fel-based Fault Identificationmentioning

confidence: 99%

“…A combination of singular perturbation theory and implicit function theorem has been incorporated in [109] to deal with the longitudinal model of an HFV in a unified manner, while conservative assumptions on the dynamic model are required in the proposed control scheme. In a more effective way, a neural backstepping controller has been proposed in [189] for a MIMO model of an HFV considering the coupling between the velocity and attitude subsystems, where a combined adaptive design and a DO (as discussed in Section 3.4.2) has been adopted.…”

Section: Cholesky Decomposition)mentioning

confidence: 99%

Neural network-based flight control systems: Present and future

Emami

Castaldi

Banazadeh

2022

Annual Reviews in Control

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Adaptive fault‐tolerant control for a class of flexible air‐breathing hypersonic vehicles

Huang

Wang

et al. 2023

Asian Journal of Control

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In this paper, a novel adaptive fault‐tolerant control (FTC) scheme is proposed for a class of flexible air‐breathing hypersonic vehicles with unknown inertial and aerodynamic parameters and even input constraints. The fault model under consideration covers the case that all actuators suffer from unknown time‐varying faults. In the controller design and stability analysis, we introduce new Lyapunov functions, some differentiable auxiliary functions, a bound estimation approach, and a Nussbaum function, which help us successfully circumvent the obstacle caused by the faults, input constraints, and flexible modes. In addition to higher reliability, the proposed scheme is able to ensure that all closed‐loop signals are globally uniformly bounded and to steer the tracking errors of altitude and velocity into predefined arbitrarily small residual sets. As a result, the tracking accuracy can be designated in advance. Simulation results illustrate the effectiveness of the proposed scheme.

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Adaptive fault tolerant control for hypersonic flight vehicle system with state constraints

Cited by 19 publications

References 32 publications

Asymmetric integral BLF based state‐constrained flight control using NN and DOB

Asymmetric integral BLF based state‐constrained flight control using NN and DOB

Neural network-based flight control systems: Present and future

Adaptive fault‐tolerant control for a class of flexible air‐breathing hypersonic vehicles

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