Sliding Mode Control Using SVM for Power Quality Enhancement in StandAlone System Based on Four-Leg Voltage

Djerioui, Ammar; Ouali, Dehimi; Ladjal, Mohamed

doi:10.22266/ijies2018.0430.29

Cited by 4 publications

(8 citation statements)

References 18 publications

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“…This particular type of cell relies on a unique, specific polymer membrane covered in extensively dispersed catalyst particles. From the anode side, hydrogen is fed into the membrane, where the catalyst causes the hydrogen atoms to release their electrons and transform into protons 𝐻 + (ions) [4,15].…”

Section: Pemfc Nonlinear Modelmentioning

confidence: 99%

“…The overall reaction becomes as described in Eq. ( 3) [4,19]: To avoid flooding and rendering the cell inoperable, the created water must be expelled [20]. In this context, a single cell generates between 0.5 and 0.9 under standard operating circumstances.…”

Section: Pemfc Nonlinear Modelmentioning

confidence: 99%

“…The polarization curve, which displays highly nonlinear relationships between voltages and current, is typically employed to express the performance of the entire cell [19,20]. One way to define a single cell's output voltage is as follows [4,20]:…”

Section: Pemfc Nonlinear Modelmentioning

confidence: 99%

“…In particular, the PEMFC systems are the most popular hydrogen energy source because they offer the essential qualities of high efficiency, International Journal of Intelligent Engineering and Systems, Vol. 16 high reliability, low operating noise, and flexible modular design together with excellent performance, quick power response, high power density, low operating temperature, and low maintenance requirements [4,5]. As a result, they are widely utilized in military environments, cars, unmanned aerial vehicles, and mobile devices [2].…”

Section: Introductionmentioning

confidence: 99%

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Development of Predictive Voltage Controller Design for PEM Fuel Cell System based on Identifier Model

2023

IJIES

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This paper presents a new development of a predictive voltage neural controller to control the stack terminal output voltage of a nonlinear proton exchange membrane fuel cell (PEMFC) system based on a neural network technique and a back-propagation learning algorithm. The main objective of this paper is to precisely and quickly identify the best control action of the hydrogen partial pressure to enhance the nonlinear performance of the fuel cell output voltage under a variable load current. This optimal control action prevents damage to the fuel cell membrane, thereby prolonging the fuel cell's lifetime. The proposed predictive voltage controller consists of three sub-controllers. The first one is the numerical feed-forward controller (NFFC), which is used to decide the steady-state hydrogen partial pressure (PH2) control action depending on the desired voltage. The second sub-controller is a feedback neural controller that uses a multi-layer perceptron (MLP) and a back-propagation learning algorithm to generate the hydrogen partial pressure feedback control action to track the desired output voltage of the fuel cell during transient conditions. The third sub-controller is the predictive control law equation, which is based on the modified Elman recurrent neural network (MERNN) as an identifier for the PEMFC model and the multi-objective performance index. From the simulation results, the proposed controller, which is composed of the three sub-controllers, has the capability to generate a precisely and quickly timed response to the hydrogen partial pressure control action in order to minimize the tracking voltage error and eliminate oscillation in the output voltage of the fuel cell. Finally, the suggested predictive voltage control strategy's numerical simulation results are then verified by comparison with those of other types of controllers in terms of the minimum number of steps ahead prediction (reducing from 10 to 1 step ahead prediction) and enhancement of the tracking voltage error by 81.8% when comparing with a predictive neural controller and improvement of the tracking voltage error by 87.5% when comparing with an inverse neural controller. Moreover, the oscillation effect in the output voltage is completely eliminated, resulting in a response without any overshoot.

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Section: Pemfc Nonlinear Modelmentioning

confidence: 99%

Section: Pemfc Nonlinear Modelmentioning

confidence: 99%

Section: Pemfc Nonlinear Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development of Predictive Voltage Controller Design for PEM Fuel Cell System based on Identifier Model

2023

IJIES

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“…Equation 6is known as sliding condition [33] [34] and it states that all the Euclidian distances from the sliding surface through all state trajectories is decreasing. This will force the trajectories towards the sliding surface.…”

Section: A Composite Transfer Functionmentioning

confidence: 99%

Sliding Mode Control for 2 Degrees of Freedom Upper Limb Rehabilitation Robotic System under Uncertainties

Ahmed,

Raza,

Hussian

et al. 2019

IJEAT

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Rehabilitation of patients suffering from post-stroke injuries via robots is now adapted word widely. The aim of this therapy is to restore and improve the dysfunction and the performance of the affected limbs doing repetitive tasks with the help of rehabilitation robots, as robots are best way to perform repetitive task without any monotony failure. Control of these rehabilitation robots is an important part to consider because of nonlinearity and uncertainty of the system. This paper presents nonlinear sliding mode controller (SMC) for controlling a 2 degrees of freedom (DOF) upper limb robotic manipulator. Sliding mode control is able to handle system uncertainties and parametric changes. One drawback of using SMC is high frequency oscillations called as chattering. This chattering can be reduced by using boundary layer technique. Experiments have been carried out under perturbed conditions and results have shown that SMC performs well and remain stable and thus proves to robust controller for upper limb robotic manipulator.

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Design of an LED Sink Driver Using a Switched-Inductor and Switched-Capacitor Buck-Boost Converter with High Voltage Gains

Eguchi

Shibata

Asadi

et al. 2020

2020 2nd International Conference on Smart Power &Amp; Internet Energy Systems (SPIES)

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Sliding Mode Control Using SVM for Power Quality Enhancement in StandAlone System Based on Four-Leg Voltage

Cited by 4 publications

References 18 publications

Development of Predictive Voltage Controller Design for PEM Fuel Cell System based on Identifier Model

Development of Predictive Voltage Controller Design for PEM Fuel Cell System based on Identifier Model

Sliding Mode Control for 2 Degrees of Freedom Upper Limb Rehabilitation Robotic System under Uncertainties

Design of an LED Sink Driver Using a Switched-Inductor and Switched-Capacitor Buck-Boost Converter with High Voltage Gains

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