Reconfigurable flight control laws for re-entry vehicles

Poderico, M.; Morani, Gianfranco; Ariola, M.

doi:10.1109/med.2013.6608698

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…In this case, the remaining degree of freedom can be used to choose the solution which is the nearest to a reference control vector u d   m (for example the one computed by the control system, u p ). More details of this Control Allocation algorithm and its implementation can be found in [7].…”

Section: The Control Allocation Modulementioning

confidence: 99%

“…In [7] reconfiguration capabilities, obtained using the robust/adaptive control system combined with the control allocation, are described with reference to the re-entry application. This method proposes a new scheme of FaultTolerant Flight Control.…”

Section: Introductionmentioning

confidence: 99%

“…Such a system detects actuator failures and provides information to the control allocation algorithms. In [7] the problem of FDI has not been addressed.…”

Section: Introductionmentioning

confidence: 99%

“…In a previous work [7], the authors proposed a simplified architecture, assuming that the information about vehicle health status was available but the FDI algorithms were not developed. Therefore this paper is an extension of the previous one with the aim of improving the FDIR architecture and showing the effectiveness of the proposed FTC strategy.…”

Section: Introductionmentioning

confidence: 99%

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Fault detection isolation and reconfiguration algorithms for atmospheric re-entry

Poderico

Morani

Corraro

2014

22nd Mediterranean Conference on Control and Automation

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This paper proposes a new Fault Tolerant Control Strategy relying on Fault Detection, Isolation and Reconfiguration (FDIR) algorithms. Adaptive Control laws are combined to Control Allocation algorithms that enable the reconfiguration of Flight Control Laws in case of actuators and/or Reaction Control System (RCS) failures. This allows achieving good robustness to possible failures occurring during flight and, at the same time, to optimize the use of a hybrid set of control effectors (i.e. aerodynamic surfaces and Reaction Control System) such to reduce thrusters fuel consumption. Fault Detection and Isolation (FDI) algorithms provide the required information about the health status of actuators/RCS thus enabling the reconfiguration of Flight Control Laws. The effectiveness of the proposed approach has been preliminarily demonstrated through a numerical analysis that accounts for both nominal and failures scenario, by using a 6Dof Model of Flying Test Bed FTB3, developed by Italian Aerospace Research Centre in the framework of Unmanned Space Vehicle (USV) Program.

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Section: The Control Allocation Modulementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Such a system detects actuator failures and provides information to the control allocation algorithms. In [7] the problem of FDI has not been addressed.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fault detection isolation and reconfiguration algorithms for atmospheric re-entry

Poderico

Morani

Corraro

2014

22nd Mediterranean Conference on Control and Automation

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Acute effects of high-intensity exercise on brain mechanical properties and cognitive function

McIlvain,

Magoon,

Clements

et al. 2024

Brain Imaging and Behavior

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Previous studies have shown that engagement in even a single session of exercise can improve cognitive performance in the short term. However, the underlying physiological mechanisms contributing to this effect are still being studied. Recently, with improvements to advanced quantitative neuroimaging techniques, brain tissue mechanical properties can be sensitively and noninvasively measured with magnetic resonance elastography (MRE) and regional brain mechanical properties have been shown to reflect individual cognitive performance. Here we assess brain mechanical properties before and immediately after engagement in a high-intensity interval training (HIIT) regimen, as well as one-hour post-exercise. We find that immediately after exercise, subjects in the HIIT group had an average global brain stiffness decrease of 4.2% (p < 0.001), and an average brain damping ratio increase of 3.1% (p = 0.002). In contrast, control participants who did not engage in exercise showed no significant change over time in either stiffness or damping ratio. Changes in brain mechanical properties with exercise appeared to be regionally dependent, with the hippocampus decreasing in stiffness by 10.4%. We also found that one-hour after exercise, brain mechanical properties returned to initial baseline values. The magnitude of changes to brain mechanical properties also correlated with improvements in reaction time on executive control tasks (Eriksen Flanker and Stroop) with exercise. Understanding the neural changes that arise in response to exercise may inform potential mechanisms behind improvements to cognitive performance with acute exercise.

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Control Allocation–Based Command Tracking–Control System for Hypersonic Re-entry Vehicle Driven by Hybrid Effecters

Song

Cai²,

Chen³

2018

J. Aerosp. Eng.

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Reconfigurable flight control laws for re-entry vehicles

Cited by 3 publications

References 7 publications

Fault detection isolation and reconfiguration algorithms for atmospheric re-entry

Fault detection isolation and reconfiguration algorithms for atmospheric re-entry

Acute effects of high-intensity exercise on brain mechanical properties and cognitive function

Control Allocation–Based Command Tracking–Control System for Hypersonic Re-entry Vehicle Driven by Hybrid Effecters

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