Fuzzy Fault Diagnosis and Accommodation System for Hybrid Fuel-Cell/Gas-Turbine Power Plant

Yang, Wu; Lee, Kwang Y.; Junker, S.; Ghezel-Ayagh, Hossein

doi:10.1109/tec.2010.2060341

Cited by 30 publications

(11 citation statements)

References 23 publications

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“…This criterion confronts the previous one; therefore, a compromise should be met. (5) The controller that achieves the least number of switching, for example, a slight loss of performance could be tolerated if the actual controller in the loop is kept, in order to avoid switching transients.…”

Section: Controller Switching Strategymentioning

confidence: 99%

“…Model‐based FDI for PEMFC systems based on consistency relations for the detection and isolation of predefined faults has been proposed in , while in , a comparison of both model‐based and data‐driven fault detection methods for fuel cells is addressed. The work in proposes a methodology to use the electrical model for fuel cell system diagnosis, while in , a fault diagnosis and accommodation system based on fuzzy logic has been developed as an effective complement for a closed‐loop scheme. Regarding FTC, Feroldi proposes an model predictive control scheme for adding fault tolerance capabilities to a two‐actuator PEMFC system.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Data‐driven fault diagnosis and robust control: Application to PEM fuel cell systems

Ocampo‐Martínez

Peña

Bianchi

et al. 2017

Intl J Robust & Nonlinear

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Summary A data‐driven methodology that includes the unfalsified control concept in the framework of fault diagnosis and isolation (FDI) and fault‐tolerant control (FTC) is presented. The selection of the appropriate controller from a bank of controllers in a switching supervisory control setting is performed by using an adequate FDI outcome. By combining simultaneous online performance assessment of multiple controllers with the fault diagnosis decision from structured hypothesis tests, a diagnosis statement regarding what controller is most suitable to deal with the current (nominal or faulty) mode of the plant is obtained. Switching strategies that use the diagnosis statement are also proposed. This approach is applied to a nonlinear experimentally validated model of the breathing system of a polymer electrolyte membrane fuel cell. The results show the effectiveness of this FDI–fault‐tolerant control data‐driven methodology. Copyright © 2017 John Wiley & Sons, Ltd.

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Section: Controller Switching Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data‐driven fault diagnosis and robust control: Application to PEM fuel cell systems

Ocampo‐Martínez

Peña

Bianchi

et al. 2017

Intl J Robust & Nonlinear

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“…For example, Kavuri and Venkatasubramanian [46,47] generalized radial units to Gaussian units and proposed methods to solve the hidden node problem. Artificial Neural Networks (ANNs) have been intensively studies during the last two decades and successfully applied to dynamic system modeling and fault diagnosis [48][49][50][51][52][53][54][55][56][57].…”

Section: Neural Network Approachmentioning

confidence: 99%

Hybrid computing techniques for fault detection and isolation, a review

Khoukhi

Khalid

2015

Computers & Electrical Engineering

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“…It improves the reliability of the hybrid power plant and the overall plant efficiency is expected to be increased [3].…”

Section: A Overview Of Hybrid Fuel-cell/gas-turbine Power Plantmentioning

confidence: 99%

Modeling and control of power conditioning system for grid-connected Fuel Cell power plant

Lee

Yang

2013

2013 IEEE Power &Amp; Energy Society General Meeting

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This paper introduces a power conditioning system (PCS) for the Fuel Cell power plant. The PCS is an interface between distributed generation and utility grid. The proposed system has DC/DC converter, DC/AC inverter, and LCL filter. The DC/DC converter and DC/AC inverter use switches that operate at high speeds. The use of detailed model with switches will decrease the simulation speed, and thus it takes long time to execute time simulations in MATLAB. This paper presents effective average models for DC/DC converter and DC/AC inverter to reduce the calculation time in MATLAB. This helps significantly in reducing execution time when implemented for a large-scale fuel cell power plant. Index Terms--Fuel cells, distributed generation, average model of converters, power conditioning system. I.

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Fuzzy Fault Diagnosis and Accommodation System for Hybrid Fuel-Cell/Gas-Turbine Power Plant

Cited by 30 publications

References 23 publications

Data‐driven fault diagnosis and robust control: Application to PEM fuel cell systems

Data‐driven fault diagnosis and robust control: Application to PEM fuel cell systems

Hybrid computing techniques for fault detection and isolation, a review

Modeling and control of power conditioning system for grid-connected Fuel Cell power plant

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