Fault Detection of continuous time linear switched systems using combination of Bond Graph method and switching observer

Kazemi, Mohammad Ghasem; Montazeri, Mohsen

doi:10.1016/j.isatra.2019.04.023

Cited by 20 publications

(15 citation statements)

References 34 publications

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“…Likewise, Hanif et al in [22] proposed a piecewise affine PI control based on the safe experimentation dynamics algorithm. While Kazemi and Montazeri in [23] showed a fault detection system using a combination of bond graph method and a switching observer. More recently, in 2020 an H-infinity adaptive neurofuzzy control method was exploited by Rigatos et al in [24].…”

Section: A "Siso Dc/dc Buck Converter-dc Motor" Systemmentioning

confidence: 99%

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Sensorless Tracking Control for a “Full-Bridge Buck Inverter–DC Motor” System: Passivity and Flatness-Based Design

et al. 2021

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A sensorless control based on the exact tracking error dynamics passive output feedback (ETEDPOF) methodology is proposed for executing the angular velocity trajectory tracking task on the "full-bridge Buck inverter-DC motor" system. When such a methodology is applied to the system, the tracking task is achieved by considering only the current sensing and by using some reference trajectories for the system. The reference trajectories are obtained by exploiting the flatness property associated with the mathematical model of the "full-bridge Buck inverter-DC motor" system. Experimental tests are developed for different desired angular velocity trajectories. With the aim of obtaining the experimental results in closed-loop, a "full-bridge Buck inverter-DC motor" prototype, Matlab-Simulink, and a DS1104 board from dSPACE are employed. The experimental results show the effectiveness of the proposed control.INDEX TERMS Motor drivers, power converters, full-bridge Buck inverter, DC motor, passivity control, differential flatness, trajectory tracking.

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Section: A "Siso Dc/dc Buck Converter-dc Motor" Systemmentioning

confidence: 99%

“…In this experiment both, the ETEDPOF control and a PID control are experimentally implemented on the built platform of the system when the nominal parameters, defined in (23) and (24), are taken into account. The desired angular velocity trajectory to be followed by the motor shaft is proposed to be,…”

Section: Experimental Testmentioning

confidence: 99%

Sensorless Tracking Control for a “Full-Bridge Buck Inverter–DC Motor” System: Passivity and Flatness-Based Design

et al. 2021

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“…Another research was exposed by Nizami et al in [24], where a neuro-adaptive backstepping control using single-layer Chebyshev polynomials based neural network was exhibited. Recently, interesting contributions have been accomplished in [25][26][27]. Hanif et al in [25] explained a safe experimentation dynamics algorithm for a data-driven piecewise affine PI control.…”

Section: Introductionmentioning

confidence: 99%

“…Yang et al in [26] studied a robust predictive control via a discrete-time reduced-order generalized proportionalintegral (GPI) observer. Meanwhile, a fault detection scheme based on a combination of switching observer and bond graph method was addressed by Kasemi and Montazeri in [27]. More recently, Rigatos et al in [28] used an adaptive neuro-fuzzy H-infinity control approach.…”

Section: Introductionmentioning

confidence: 99%

Robust Flatness Tracking Control for the “DC/DC Buck Converter‐DC Motor” System: Renewable Energy‐Based Power Supply

et al. 2021

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The design of a robust flatness-based tracking control for the DC/DC Buck converter-DC motor system is developed in this paper. The design of the control considers the dynamics of a renewable energy power source that plays the role of the primary power supply associated with the system. The performance and robustness of the control is verified through simulations via MATLAB-Simulink when abrupt changes in some parameters of the system are taken into account. Also, experiments are performed by using a built prototype of the DC/DC Buck converter-DC motor system, a TDK-Lambda G100-17 programmable DC power supply, MATLAB-Simulink, and the DS1104 board from dSPACE. In this regard, the TDK-Lambda G100-17 is implemented with the aim of emulating photovoltaic panels through the solar array mode for generating the power supply of the system. Thus, both simulations and experiments show the effectiveness of the proposed control scheme.

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“…Based on this assumption, the modes between subsystem and residual generator are perfectly matched, which thus excludes the influence of system switching on the fault detection. In [ 43 , 44 ], the model-based approaches are investigated for switched systems with the determinate switching law, and in [ 45 ], a combination of switching observer and Bond Graph method is proposed while the switching signal is known. In [ 46 , 47 ], parity space method is applied to fault detection of the switching system, but the possibility that the switching signal is unknown is not considered.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Scheme for Fault Detection of Discrete-Time Switched Systems

Zhao

Luo

2021

Sensors

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This paper is concerned with the fault detection issue for a class of discrete-time switched systems via the data-driven approach. For the fault detection of switched systems, it is inevitable to consider the mode matching problem between the activated subsystem and the executed residual generator since the mode mismatching may cause a false fault alarm in all probability. Frequently, studies assume that the switching laws are available to the residual generator, by which the residual generator keeps the same mode as the system plant and then the mode mismatching is excluded. However, this assumption is conservative and impractical because many switching laws are hard to acquire in practical applications. This work focuses on the case of switched systems with unavailable switching laws. In view of the unavailability of switching information, the mode recognition is considered for the fault detection process and meanwhile, sufficient conditions are presented for the mode distinguishability. Moreover, a novel decision logic for the fault detection is proposed, based on which new algorithms are established for the data-driven realization. Finally, a benchmark case on a three-tank system is used to illustrate the feasibility and usefulness of the obtained results.

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Fault Detection of continuous time linear switched systems using combination of Bond Graph method and switching observer

Cited by 20 publications

References 34 publications

Sensorless Tracking Control for a “Full-Bridge Buck Inverter–DC Motor” System: Passivity and Flatness-Based Design

Sensorless Tracking Control for a “Full-Bridge Buck Inverter–DC Motor” System: Passivity and Flatness-Based Design

Robust Flatness Tracking Control for the “DC/DC Buck Converter‐DC Motor” System: Renewable Energy‐Based Power Supply

A Data-Driven Scheme for Fault Detection of Discrete-Time Switched Systems

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