Design of FDI filter for an aircraft control system

Szászi, István; Kulcsár, Balázs; Balas, Gary J.; Bokor, József

doi:10.1109/acc.2002.1024596

Cited by 12 publications

(4 citation statements)

References 12 publications

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“…Donders (2002) applied Kalman Filter and Interacting Multiple-Model estimators to the wind turbine FDI problem. H ∞ /H − techniques for observer design were used by Wei and Verhaegen (2008) and Szaszi et al (2002). Another method of obtaining residuals is to compare the redundant information about the system if the system has some physical redundancy built in it.…”

Section: Introductionmentioning

confidence: 99%

Wind Turbine Fault Detection Using Counter-Based Residual Thresholding

Ozdemir

Seiler²,

Balas

2011

IFAC Proceedings Volumes

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This paper investigates application of model-based fault detection techniques on wind turbines. Fault residuals are generated through physically redundant sensors, parity equations and common filtering methods. Up-down counters are used for decisioning on these fault residuals. These simple counters are commonly used in the aerospace industry to improve missed detection rates. These techniques constitute an easily implementable fault detection and isolation system on an industrial turbine. The performance of the developed algorithm is evaluated on a model of a commercial sized 4.8MW wind turbine. Realistic fault scenarios in the sensing, actuation and drivetrain subsystems are considered. It is seen that most faults can be detected with fast detection times and minimal false alarms without implementation of more complex filtering and detection techniques on residuals.

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Section: Introductionmentioning

confidence: 99%

Wind Turbine Fault Detection Using Counter-Based Residual Thresholding

Ozdemir

Seiler²,

Balas

2011

IFAC Proceedings Volumes

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“…The aircraft system under consideration in this paper can be modeled via the following state space representation [1], [5], [8], [30], [31]: (1) where denotes the uncertain state matrix, for represents the uncertain input matrix, is the known output matrix, is a vector of control inputs, 1 and represents an unknown, nonlinear disturbance.…”

Section: Aircraft Model and Propertiesmentioning

confidence: 99%

Asymptotic Tracking for Aircraft via Robust and Adaptive Dynamic Inversion Methods

MacKunis

Patre

Kaiser

et al. 2010

IEEE Trans. Contr. Syst. Technol.

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Abstract-Two asymptotic tracking controllers are designed in this paper, which combine model reference adaptive control and dynamic inversion methodologies in conjunction with the robust integral of the signum of the error (RISE) technique for output tracking of an aircraft system in the presence of parametric uncertainty and unknown, nonlinear disturbances, which are not linearly parameterizable (non-LP). The control designs are complicated by the fact that the control input is multiplied by an uncertain, non-square matrix. A robust control design is presented first, in which partial knowledge of the aircraft model along with constant feedforward estimates of the unknown input parameters are used with a robust control term to stabilize the system. Motivated by the desire to reduce the need for high-gain feedback, an adaptive extension is then presented, in which feedforward adaptive estimates of the input uncertainty are used. These results show how asymptotic tracking control can be achieved for a nonlinear system in the presence of a non-square input matrix containing parametric uncertainty and nonlinear, non-LP disturbances. Asymptotic output tracking is proven via Lyapunov stability analysis, and high-fidelity simulation results are provided to verify the efficacy of the proposed controllers.

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“…The LPV theory has allowed to extend linear methods to nonlinear domains [6]. LPV modeling is used to study nonlinear systems, multiple models or switched models [7].…”

Section: Introductionmentioning

confidence: 99%

Actuator Fault Reconstruction based Adaptive Polytopic Observer for a Class of Continuous-Time LPV Systems

Houimli¹,

Bedioui²,

Besbes³

2018

Adv. sci. technol. eng. syst. j.

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This paper is an extension of work originally presented in conference name. The goal is to propose new fault detection and fault isolation techniques for a polytypic linear parametervarying system (LPV). In this work, an adaptive observer design is formulated for a given polyquadratic Lyapunov function. Subsequently, new sufficient conditions are given in terms of Linear Matrix Inequalities (LMIs). To show the effectiveness of the proposed algorithm, an illustrative example is included.

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Design of FDI filter for an aircraft control system

Cited by 12 publications

References 12 publications

Wind Turbine Fault Detection Using Counter-Based Residual Thresholding

Wind Turbine Fault Detection Using Counter-Based Residual Thresholding

Asymptotic Tracking for Aircraft via Robust and Adaptive Dynamic Inversion Methods

Actuator Fault Reconstruction based Adaptive Polytopic Observer for a Class of Continuous-Time LPV Systems

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