Nussbaum-based fuzzy adaptive nonlinear fault-tolerant control for hypersonic vehicles with diverse actuator faults

Hu, Chaofang; Zhou, Xianpeng; Sun, Bao; Liu, Wenjing; Zong, Qun

doi:10.1016/j.ast.2017.10.002

Cited by 41 publications

(8 citation statements)

References 36 publications

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“…Compared with the method in [16,31,32], each weight update requires a lot of calculation. In this article, only one online learning parameter is needed by using the norm estimation approach, which makes the online calculation of the system significantly reduced.…”

Section: Remarkmentioning

confidence: 99%

Fuzzy-Approximation-Based Novel Back-Stepping Control of Flexible Air-Breathing Hypersonic Vehicles with Nonaffine Models

2019

International Journal of Aerospace Engineering

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This article investigates a novel fuzzy-approximation-based nonaffine control strategy for a flexible air-breathing hypersonic vehicle (FHV). Firstly, the nonaffine models are decomposed into an altitude subsystem and a velocity subsystem, and the nonaffine dynamics of the subsystems are processed by using low-pass filters. For the unknown functions and uncertainties in each subsystem, fuzzy approximators are used to approximate the total uncertainties, and norm estimation approach is introduced to reduce the computational complexity of the algorithm. Aiming at the saturation problem of actuator, a saturation auxiliary system is designed to transform the original control problem with input constraints into a new control problem without input constraints. Finally, the superiority of the proposed method is verified by simulation.

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Section: Remarkmentioning

confidence: 99%

Fuzzy-Approximation-Based Novel Back-Stepping Control of Flexible Air-Breathing Hypersonic Vehicles with Nonaffine Models

2019

International Journal of Aerospace Engineering

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“…The forces and moment are expressed as follows:

({, \begin{array}{l} T = 0.5 ρ V^{2} S C_{T}, \\ D = 0.5 ρ V^{2} S C_{D}, \\ L = 0.5 ρ V^{2} S C_{L}, \\ M_{y y} = 0.5 ρ V^{2} S \overset{c}{true} ((), C_{M} ((), α) + C_{M} ((), δ_{e}) + C_{M} ((), q)), \end{array})

The force and moment coefficients are given as follows:

({, \begin{array}{l} C_{T} = ({, \begin{matrix} 0.02576 δ_{T}, & δ_{T} < 1, \\ 0.0224 + 0.00336 δ_{T}, & δ_{T} \geq 1, \end{matrix}) \\ C_{D} = 0.6450 α^{2} + 0.0043378 α + 0.003772, \\ C_{L} = 0.6203 α, \\ C_{M} ((), α) = - 0.035 α^{2} + 0.004337 α + 5.3261 \times 10^{- 6}, \\ C_{M} ((), δ_{e}) = c_{e} ((), δ_{e} - α), \\ C_{M} ((), q) = ((), \overset{c}{true} false/ 2 V) q ((), - 6.796 α^{2} + 0.3015 α - 0.2289), \end{array})

where δ e and δ T represent the elevator deflection and throttle setting, respectively; C T , C D , and C L denote the coefficient of throttle, drag, and lift, respectively; and C M (·) is the pitch moment coefficient with respect to (·). More parameter details can be found in the work of Hu et al…”

Section: Problem Formulationmentioning

confidence: 99%

“…where e and T represent the elevator deflection and throttle setting, respectively; C T , C D , and C L denote the coefficient of throttle, drag, and lift, respectively; and C M (·) is the pitch moment coefficient with respect to (·). More parameter details can be found in the work of Hu et al 5 In actual flight, multisensor faults may occur when the HFV faces a harsh environment or experiences drastic changes in parameters. However, the HFV longitudinal model is with the characteristics of high nonlinearity and strong coupling, based on which multisensor faults modeling is of great difficulty.…”

Section: Longitudinal Dynamics Of Hfvmentioning

confidence: 99%

“…Hypersonic flight vehicles (HFVs) with characteristics of uncertainty, strong nonlinearity and coupling, and nonminimum phase have attracted increasing attention over the last decades . Changes in atmospheric conditions as well as physical and atmospheric parameters often lead to actuator, sensor, and component faults in practical applications, thereby causing a catastrophic effect to the flight performance of HFVs . Furthermore, HFVs are more sensitive to the influence of external disturbances and uncertainties than other aircraft; thus, they have higher demand for robustness .…”

Section: Introductionmentioning

confidence: 99%

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Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Chen

Gong

2019

Intl J Robust & Nonlinear

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Summary This study proposes an improved adaptive fault diagnosis and compensation scheme for multisensor faults of hypersonic flight vehicles (HFVs). The faults are detected and isolated through a series of sensor output residuals and thresholds that consider observation error and disturbances. Via an adaptive augmented observer, the faults are estimated accurately and a time‐varying disturbance is handled by an additional differential part. Sensor faults are compensated on the basis of estimation results, and disturbances are considered in the fault‐tolerant control (FTC) design, thereby improving the tracking accuracy of the altitude and velocity and robustness with respect to external disturbances for HFVs. The stability of diagnosis and FTC is analyzed by Lyapunov theory. Numerical simulation results explain the validity of the proposed diagnosis and compensation methods.

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“…Beyond the above model-based design methods, there is a different design philosophy in data-driven monitoring and safety control of industrial cyber-physical systems, which takes advantage of historical input-output data rather than the demanding knowledge about the systems' mechanism models [15]. Reference [16]- [18] utilizes fuzzy adaptive control techniques to realize AFTC when subjected to actuator faults. Kamal et al proposed a fuzzy multi-observer switching control strategy for fault tolerant control of variable-speed wind energy conversion systems in the presence of wide wind variation, wind disturbance, parametric uncertainties, and sensors faults [19].…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Nonlinear Dynamic Inversion for Attitude Control of a Structurally Damaged Aircraft

Tan

Liu

et al. 2020

IEEE Access

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Structural damage induces extensive parameter changes of an aircraft, which leads to the mismatch problem between the offline model and a flying aircraft. Due to extensive parameter changes, motion of a damaged aircraft is difficultly described with a mathematical model. This article uses disturbances in accelerations and angular accelerations to quantify the effects of extensive parameter changes, and derives a mathematical model for a damaged aircraft. Provided that the flight controller of a damaged aircraft has a fixed structure, the mismatch problem may cause the aircraft unstable. Based on the proposed mathematical model, this article proposed a reconfigurable nonlinear dynamic inversion (RNDI) controller for attitude control of a structurally damaged aircraft, which synthesizes a nonlinear disturbance observer (NDO) with a modified nonlinear dynamic inversion (NDI) controller. The NDO is explored to estimate the disturbances in angular accelerations. Afterwards, the estimations are fed into the modified NDI controller realizes control structure reconfiguration. Conventional NDI control law and model reference adaptive control (MRAC) law are compared, and simulation results demonstrate that the proposed RNDI control law is robust to structural damage and possesses satisfactory control performance. INDEX TERMS active fault-tolerant control, nonlinear dynamic inversion, nonlinear disturbance observer, reconfigurable controller, attitude control, adaptive control, structurally damaged aircraft

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Nussbaum-based fuzzy adaptive nonlinear fault-tolerant control for hypersonic vehicles with diverse actuator faults

Cited by 41 publications

References 36 publications

Fuzzy-Approximation-Based Novel Back-Stepping Control of Flexible Air-Breathing Hypersonic Vehicles with Nonaffine Models

Fuzzy-Approximation-Based Novel Back-Stepping Control of Flexible Air-Breathing Hypersonic Vehicles with Nonaffine Models

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

Reconfigurable Nonlinear Dynamic Inversion for Attitude Control of a Structurally Damaged Aircraft

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