Design of robust fuzzy fault detection filter for polynomial fuzzy systems with new finite frequency specifications

Chibani, Ali; Chadli, Mohammed; Ding, Steven X.; Braïek, Naceur Benhadj

doi:10.1016/j.automatica.2018.03.024

Cited by 83 publications

(42 citation statements)

References 37 publications

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“…[147,148]. However, for some practical systems, fault and disturbance frequencies ranges are known beforehand, which motivated recent research on filter design in a finite-frequency domain [149][150][151], using the so-called generalized Kalman-Yakubovich-Popov (GKYP) lemma [152]. Another recent line of research worth of mentioning is the one that investigates the behavior of the fault detection observer when unmeasurable scheduling parameters are considered, see for example, Ref.…”

Section: Residual Generation For Fault Detectionmentioning

confidence: 99%

“…where y c (t) is the compensated system output andf s (t) is the sensor fault estimate. Since (149) and (151) describe an autonomous convex system, the integrated FE/FTC design can be formulated as an LMI-based stabilization problem (H ∞ optimization if there are uncertainties and/or disturbances).…”

Section: Fault Tolerant Control Based On Controller Reconfigurationmentioning

confidence: 99%

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A Review of Convex Approaches for Control, Observation and Safety of Linear Parameter Varying and Takagi-Sugeno Systems

2019

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This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).

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Section: Residual Generation For Fault Detectionmentioning

confidence: 99%

Section: Fault Tolerant Control Based On Controller Reconfigurationmentioning

confidence: 99%

A Review of Convex Approaches for Control, Observation and Safety of Linear Parameter Varying and Takagi-Sugeno Systems

2019

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“…Therefore, many other significant and effective approaches have been developed [20], [29]. Some examples include H 2 filtering [31], H ∞ filtering [30], [33], mixed H ∞ and passive filtering [26], H − /H ∞ filter design for discrete T-S fuzzy system [8], filter design for polynomial fuzzy systems [6], robust observer design for unknown input T-S models [9], fault detection filter design for T-S fuzzy systems in the finite-frequency domain, which was resolved in [7], and efficient adaptive filter design for the signal processing problem, which was proposed in [16]. Of these filtering methods, two approaches are particularly common: robust H 2 filtering [11] and H ∞ filtering [32].…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Fuzzy Filtering for Nonlinear Dynamic Systems via Reduced-Order Approach

Wen

Shi

et al. 2019

IEEE Trans. Fuzzy Syst.

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“…Some signal processing methods are applied in order to preprocess the raw vibration signals [12,[34][35][36]. Chibani et al [37] designed a novel filter in the finite frequency range to overcome the conservatism generated. Chadli et al [38] proposed a novel fault detection and isolation filter for multi-agent systems.…”

Section: Introductionmentioning

confidence: 99%

Rolling Bearing Incipient Fault Detection Based on a Multi-Resolution Singular Value Decomposition

Luo

Zhang

2019

Applied Sciences

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The periodic impulse characteristics caused by rolling bearing damage are weak in the incipient failure stage. Thus, these characteristics are always drowned out by background noise and other harmonic interference. A novel approach based on multi-resolution singular value decomposition (MRSVD) is proposed in order to extract the periodic impulse characteristics for incipient fault detection. With the MRSVD method, the vibration signal is first decomposed to obtain a group of approximate signals and detailed signals with different resolutions. The first detail signal is mainly composed of noise and the last approximate signal is mainly composed of harmonic interference. Combined with the kurtosis index, the hidden periodic impulse signal will be extracted from the detail signals (in addition to the first detail signal). Thus, the incipient fault detection of a rolling bearing can be fulfilled according to the envelope demodulation spectrum of the extracted periodic impulse signal. The effectiveness of the proposed method has been demonstrated with both simulation and experimental analyses.

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Design of robust fuzzy fault detection filter for polynomial fuzzy systems with new finite frequency specifications

Cited by 83 publications

References 37 publications

A Review of Convex Approaches for Control, Observation and Safety of Linear Parameter Varying and Takagi-Sugeno Systems

A Review of Convex Approaches for Control, Observation and Safety of Linear Parameter Varying and Takagi-Sugeno Systems

Event-Triggered Fuzzy Filtering for Nonlinear Dynamic Systems via Reduced-Order Approach

Rolling Bearing Incipient Fault Detection Based on a Multi-Resolution Singular Value Decomposition

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