Robust fault diagnosis of proton exchange membrane fuel cells using a Takagi-Sugeno interval observer approach

Rotondo, Damiano; Fernandez-Canti, Rosa M.; Tornil-Sin, Sebastiàn; Blesa, Joaquim; Puig, Vicenç

doi:10.1016/j.ijhydene.2015.12.071

Cited by 65 publications

(34 citation statements)

References 46 publications

(56 reference statements)

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“…The fuel cell converts the chemical energy into electricity by consuming oxygen and hydrogen provided by air and hydrogen supply system. The linear model used in this paper can be found in Rotondo et al [2016]. It is derived from the nonlinear model presented in Pukrushpan et al [2004] under the following assumptions: the stack temperature T st is constant; the temperature and humidity of the inlet reactant flows are perfectly controlled; the anode and cathode volumes of multiple fuel cells are lumped as a single stack anode and cathode volumes; all the reactant behave as ideal gases.…”

Section: Numerical Examplementioning

confidence: 99%

“…A state space representation of order 9 is presented in Rotondo et al [2016] with the following state variables: mass of oxygen (m O2 ), mass of hydrogen (m H2 ), mass of nitrogen (m N2 ), air mass in the supply manifold (m sm ), air pressure in the supply manifold (p sm ), air pressure in the return manifold (p rm ), compressor speed (ω cp ), mass of water in the anode (m w,an ) and in the cathode (m w,ca ). An Euler discretization has been performed with the sample time T s = 0.04s to obtain the following discrete model:…”

Section: Fig 1 Fuel Cell Systemmentioning

confidence: 99%

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Interval Kalman filter enhanced by positive definite upper bounds

et al. 2017

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A method based on the interval Kalman filter for discrete uncertain linear systems is presented. The system under consideration is subject to bounded parameter uncertainties not only in the state and observation matrices, but also in the covariance matrices of Gaussian noises. The gain matrix provided by the filter is optimized to give a minimal upper bound on the state estimation error covariance for all admissible uncertainties. The state estimation is then determined by using interval analysis in order to enclose the set of all possible solutions with respect to the classical Kalman filtering structure.

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Section: Numerical Examplementioning

confidence: 99%

Section: Fig 1 Fuel Cell Systemmentioning

confidence: 99%

Interval Kalman filter enhanced by positive definite upper bounds

et al. 2017

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“…changes in the effectiveness of the faulty actuators, and stuck faults, where the inputs delivered by the faulty actuators are blocked to constant values. In the first case, the generic subsystem in (14) becomes as follows:…”

Section: Takagi-sugeno Faulty Modelmentioning

confidence: 99%

“…Some recent works have investigated fault diagnosis [11][12][13][14] and health monitoring [15] strategies for PEM fuel cells, with the aim of obtaining valuable information that could be used to extend the lifetime of the system, thereby avoiding damage in the equipment. Hence, it is interesting to add some fault tolerant capabilities to the control system, in order to maintain the fuel cell operating even in the presence of faults [16,17].…”

Section: Introductionmentioning

confidence: 99%

Fault tolerant control of a proton exchange membrane fuel cell using Takagi–Sugeno virtual actuators

Rotondo

Nejjari

Puig

2016

Journal of Process Control

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In this paper, a fault tolerant control (FTC) strategy for proton exchange membrane (PEM) fuel cells based on the use of virtual actuators and the TakagiSugeno (TS) approach is proposed. The overall solution relies on adding a virtual actuator in the control loop to hide the fault from the controller point of view, allowing it to see the same plant as before the fault, such that the stability and some desired performances are preserved. The proposed methodology is based on the use of a reference model, where the resulting nonlinear error model is brought to a Takagi-Sugeno form using a gridding approach. The TS model is suitable for designing a controller using linear matrix inequalities (LMI)-based techniques, such that the resulting closed-loop error system is stable with poles placed in some desired region of the complex plane. Simulation results are used to show the effectiveness of the proposed approach.

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“…Using the knowledge about the boundedness of the uncertainty, an interval observer computes the lower and upper bounds for the state, which are compatible with the uncertainty . A successful framework for interval observer design is based on the monotone system theory, proposed at first by Olivier et al, and further investigated by Efimov et al, Rotondo et al, and Efimov et al()…”

Section: Introductionmentioning

confidence: 99%

Fault tolerant control of uncertain dynamical systems using interval virtual actuators

Rotondo

Cristofaro

Johansen

2017

Intl J Robust & Nonlinear

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This is the peer reviewed version of the following article: Rotondo D, Cristofaro A, Johansen TA. Fault tolerant control of uncertain dynamical systems using interval virtual actuators. Int J Robust Nonlinear Control. 2018;28:611–624, which has been published in final form at https://doi.org/10.1002/rnc.3888. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.In this paper, a model reference fault tolerant control strategy based on a reconfiguration of the reference model, with the addition of a virtual actuator block, is presented for uncertain systems affected by disturbances and sensor noise. In particular, this paper (1) extends the reference model approach to the use of interval state observers, by considering an error feedback controller, which uses the estimated bounds for the error between the real state and the reference state, and (2) extends the virtual actuator approach to the use of interval observers, which means that the virtual actuator is added to the control loop to preserve the nonnegativity of the interval estimation errors and the boundedness of the involved signals, in spite of the fault occurrence. In both cases, the conditions to assure the desired operation of the control loop are provided in terms of linear matrix inequalities. An illustrative example is used to show the main characteristics of the proposed approach.Peer ReviewedPostprint (author's final draft

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Robust fault diagnosis of proton exchange membrane fuel cells using a Takagi-Sugeno interval observer approach

Cited by 65 publications

References 46 publications

Interval Kalman filter enhanced by positive definite upper bounds

Interval Kalman filter enhanced by positive definite upper bounds

Fault tolerant control of a proton exchange membrane fuel cell using Takagi–Sugeno virtual actuators

Fault tolerant control of uncertain dynamical systems using interval virtual actuators

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