A Tool for Industrial Verification and Benchmarking of FDD/FTC Designs

Fernández, Vicente; Montaño, J.; Recupero, Cristina; Kerr, Murray; Rosa, Paulo; Boada-Bauxell, Josep; Dalbies, Laurent

doi:10.1016/j.ifacol.2015.09.658

Cited by 9 publications

(17 citation statements)

References 7 publications

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“…The SIMPLAT infrastructure is in turn based on the MATLAB/Simulink modeling and simulation environment and provides all the basic functionalities needed by a FES tool so that project‐specific elements can be rapidly built on top of it. The SIMPLAT operation largely relies on its XML database, which stores the model, scenario, and simulation parameters …”

Section: Design and Evaluation Resultsmentioning

confidence: 99%

“…Remark 5. Note comparing Equation 58 with the general structure in Equation 4, it follows in this example B f 1 = 0. From Theorem 1, the nominal performance is retained, and the "small-gain theorem" condition is automatically satisfied (and therefore, the sliding surface can be established to be stable in the presence of faults/failures).…”

Section: Control Law Designmentioning

confidence: 93%

“…The SIMPLAT operation largely relies on its XML database, which stores the model, scenario, and simulation parameters. 58…”

Section: Reconfigure Fesmentioning

confidence: 99%

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Development and evaluation of an integral sliding mode fault‐tolerant control scheme on the RECONFIGURE benchmark

Chen

Alwi

Edwards

2017

Intl J Robust & Nonlinear

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Summary This paper describes the development, application, and evaluation of a linear parameter‐varying integral sliding mode control allocation scheme to the Reconfiguration of Control in Flight for Integral Global Upset Recovery benchmark model to deal with an actuator failure/fault scenario. The proposed scheme has the capability to maintain close to nominal (fault free) load factor control performance in the face of elevator failures/faults by including a retrofitted integral sliding mode term and then rerouting (via control allocation) the augmented control signal to healthy elevators without reconfiguring the baseline controller. In order to mitigate any chattering appearing in the elevator demands, the retrofitted signal is based on a super‐twisting sliding mode structure. This produces a control signal that is continuous and does not have the discontinuous switching nature of traditional sliding mode schemes. The scheme is evaluated using an industrial Functional Engineering Simulator developed as part of the Reconfiguration of Control in Flight for Integral Global Upset Recovery project. Monte Carlo campaign results are shown to demonstrate the performance of the proposed scheme.

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Section: Design and Evaluation Resultsmentioning

confidence: 99%

Section: Control Law Designmentioning

confidence: 93%

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Development and evaluation of an integral sliding mode fault‐tolerant control scheme on the RECONFIGURE benchmark

Chen

Alwi

Edwards

2017

Intl J Robust & Nonlinear

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“…For the dynamic manoeuvre the pilot stick command is a doublet signal which varies from −1 deg to +1 deg. The simulation data for various operating conditions has been harvested from the functional engineering simulator (FES) [36] developed by the other industrial partner of the project, Deimos; and used to test the performance of the observer.…”

Section: Reconfigure Fesmentioning

confidence: 99%

Fault detection in uncertain LPV systems with imperfect scheduling parameter using sliding mode observers

Chandra¹,

Alwi

Edwards

2017

European Journal of Control

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This paper presents a sliding mode fault detection scheme for linear parameter varying (LPV) systems with uncertain or imperfectly measured scheduling parameters. In the majority of LPV systems, it is assumed that the scheduling parameters are exactly known. In reality due to noise or possibly faulty sensors, it is sometimes impossible to have accurate knowledge of the scheduling parameters and a design based on the assumption of perfect knowledge of the scheduling parameters cannot be guaranteed to work well in this situation. This paper proposes a sliding mode observer scheme to reconstruct actuator and sensor faults in a situation where the scheduling parameters are imperfectly known. The efficacy of the approach is demonstrated on simulation data taken from the nonlinear RECONFIGURE benchmark model . One approach to extending linear methods to make them work effectively across the whole plant operating range is to design (linear) observers at select operating points, and then schedule the gains with respect to certain parameters [4]. One of the main difficulties with gain scheduling is the selection of the operating points and how to choose the gains at intermediate points. Furthermore, formally, between the operating points the stability of the observer cannot be guaranteed.A more rigorous alternative approach is based on so-called linear parameter varying (LPV) system designs. In the LPV approach the gains are automatically scheduled with respect to the plant varying parameters. Another advantage is many nonlinear systems can be naturally approximated by LPV systems [13] [20]). However in all these papers the scheduling parameters are assumed to be perfectly known. However in reality this may not be the case: for example inaccurate sensors and/or faults can lead to imperfect knowledge of the parameters. The use of this corrupted information will affect the performance of the observer. The design of Luenberger-like observers in scenarios involving uncertain scheduling parameters has been investigated. In [21], using a Linear matrix inequality (LMI) framework an LPV observer was proposed. Later, a controller and a combined controllerobserver scheme for inexact continuous LPV polytopic systems was presented in [22], [23]. In [24], [25] H ∞ filters were employed to deal with uncertainty in the scheduling parameters; exploiting parameter dependent LMI methods. More recently, an H ∞ filter has been proposed to deal with both additive and multiplicative uncertainties in the LPV parameters in [26]. Recent applications of these ideas to aerospace systems have been explored in [27], [28]. A fault reconstruction scheme for LPV systems with perfect scheduling parameter knowledge, using H ∞ methods has been investigated in [29]. Very few papers have addressed specifically the fault reconstruction problem for LPV systems with uncertain scheduling parameters, notable exceptions are [30]. To the authors' knowledge,

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“…• In order to facilitate industrial validation and verification (V&V), the algorithm implementation needs to use an Airbus graphical symbol library called SAO (Specification Assistee par Ordinateur). This library allows automatic code generation for the FCCs used by Airbus, but includes a significantly limited set of mathematical operation blocks [26], [27]. Such a strict constraint limits the complexity level of the implemented algorithm to be compliant with the actual FCCs.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Fault-Tolerant Moving Horizon Air Data Estimation for the RECONFIGURE Benchmark

Wan

Keviczky

2019

IEEE Trans. Contr. Syst. Technol.

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A Tool for Industrial Verification and Benchmarking of FDD/FTC Designs

Cited by 9 publications

References 7 publications

Development and evaluation of an integral sliding mode fault‐tolerant control scheme on the RECONFIGURE benchmark

Development and evaluation of an integral sliding mode fault‐tolerant control scheme on the RECONFIGURE benchmark

Fault detection in uncertain LPV systems with imperfect scheduling parameter using sliding mode observers

Real-Time Fault-Tolerant Moving Horizon Air Data Estimation for the RECONFIGURE Benchmark

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