Differential geometry based active fault tolerant control for aircraft

Castaldi, Paolo; Mimmo, Nicola; Simani, Silvio

doi:10.1016/j.conengprac.2013.12.011

Cited by 77 publications

(66 citation statements)

References 14 publications

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“…Already suggested by the authors also in the aerospace framework [10], it was extended by the same authors to the active fault tolerant control for the same wind farm simulator [11], but it is considered here only for comparison purpose.…”

Section: Introductionmentioning

confidence: 99%

Data–Driven Fault Diagnosis of a Wind Farm Benchmark Model

Simani¹,

Castaldi²,

Farsoni³

2017

Preprint

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Abstract:The fault diagnosis of wind farms has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of a wind park benchmark model, and it considers viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, noise, uncertainty and disturbances. In particular, the proposed data-driven solutions rely on fuzzy models and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive with exogenous input models, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind farm installation. The achieved performances are also compared with those of a model-based approach relying on nonlinear differential geometry tools. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.

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Section: Introductionmentioning

confidence: 99%

Data–Driven Fault Diagnosis of a Wind Farm Benchmark Model

Simani¹,

Castaldi²,

Farsoni³

2017

Preprint

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“…It is able to deal with unforeseen faults and has the potential to achieve optimal performance for 2 Journal of Control Science and Engineering different system operating scenarios. Compared to PFTC, the AFTC method has a better overall performance and is more flexible in design, so it is used more widely [12][13][14][15][16]. In AFTC, the model-based method, the knowledge-based method, the data-based method, and other methods can be adopted [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Active Fault Tolerant Control Based on a Novel Tracking Differentiator for Elevating Stage Control System

Mao¹,

Li²,

Feng³

2018

Journal of Control Science and Engineering

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In view of the speed sensor faults in elevating stage control system, an active fault tolerant control approach based on a novel tracking differentiator is proposed in this paper. First, the analytical redundancy relationship between the velocity and displacement signals in a dual closed loop control system is used to detect a fault. When the deviation between the differential of normal displacement sensor signal and the fault speed sensor output exceeds a certain threshold value, a fault can be considered to occur. Secondly, after a fault is detected, the output of the fault sensor is replaced immediately with the differential signal of the output from a normal sensor to ensure the safety of the postfault system. In the process of signal differential, considering the drawbacks of the traditional method which uses inertial element to approximate differentiator and complex parameter tuning of Han's Tracking Differentiator (TD), a novel tracking differentiator based on hyperbolic tangent function (Tanh-TD) is designed. Thirdly, in order to avoid the switching vibration and improve the reliability of FDD, a continuous smooth switching tactic based on exponential function is constructed. The simulation results show that the fault diagnosis method is simple and timely, the designed tracking differentiator is fast and effective, and the effect of the fault tolerant control based on smooth switching strategy is also satisfactory.

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“…Unknown input observers [9] are also applied to detect and isolate the sensor faults. Castaldi et al [10,11] propose a geometric approach for the FDI of aircraft sensors. Sliding Mode Observers (SMOs) [12,13] are used to reconstruct the sensor faults.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear aircraft sensor fault reconstruction in the presence of disturbances validated by real flight data

Kampen

Visser

et al. 2016

Control Engineering Practice

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Extended Kalman Filter to estimate the states and faults of the aircraft. Simulation results demonstrate the effectiveness of the proposed approach compared to an approach using an airspeed-based kinematic model. Furthermore, the major contribution is that the proposed approach is validated using real flight test data including the presence of external disturbances such as turbulence. Three flight scenarios are selected to test the performance of the proposed approach. It is shown that the proposed approach is robust to model uncertainties, unmodelled dynamics and disturbances such as time-varying wind and turbulence. Therefore, the proposed approach can be incorporated into aircraft Fault Detection and Isolation systems to enhance the performance of the aircraft.

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Differential geometry based active fault tolerant control for aircraft

Cited by 77 publications

References 14 publications

Data–Driven Fault Diagnosis of a Wind Farm Benchmark Model

Data–Driven Fault Diagnosis of a Wind Farm Benchmark Model

Active Fault Tolerant Control Based on a Novel Tracking Differentiator for Elevating Stage Control System

Nonlinear aircraft sensor fault reconstruction in the presence of disturbances validated by real flight data

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Differential geometry based active fault tolerant control for aircraft

Cited by 77 publications

References 14 publications

Data&ndash;Driven Fault Diagnosis of a Wind Farm Benchmark Model

Data&ndash;Driven Fault Diagnosis of a Wind Farm Benchmark Model

Active Fault Tolerant Control Based on a Novel Tracking Differentiator for Elevating Stage Control System

Nonlinear aircraft sensor fault reconstruction in the presence of disturbances validated by real flight data

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Product

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Data–Driven Fault Diagnosis of a Wind Farm Benchmark Model

Data–Driven Fault Diagnosis of a Wind Farm Benchmark Model