Backstepping Control Associated to Modified Space Vector Modulation for Quasi Z-source Inverter Fed by a PEMFC

Herizi, O.; Barkat, Said

doi:10.18280/ejee.210201

Cited by 3 publications

(7 citation statements)

References 15 publications

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“…To design the state augmented adaptive backstepping control method, the equations related to the error are generated, and an additional scenario is considered in the equations of the system using error integration. In the following step, system equations are divided into three subsystems [35]. The aim behind this stage is to stabilize these subsystems with the help of the Lyapunov function.…”

Section: State Augmented Adaptive Backstepping Methodsmentioning

confidence: 99%

“…Backstepping control (BSC) method can reach desirable prospects and provide better stability insurance for the operation [33,34]. Adaptive BSC (ABSC) includes the benefits of the conventional backstepping method; also, it has been improved in dynamics by the Lyapunov stability characteristics, leading to a self-learning robust (SLR) controller [35][36][37][38]. It should be noted that the most beneficial aspect of ABSC relates to its systematic and recursive design stage for designing the feedback controller.…”

Section: Introductionmentioning

confidence: 99%

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Robust adaptive backstepping control of H‐bridge inverter based on type‐2 fuzzy optimization of parameters

Azarinfar,

Khosravi,

Soroush

et al. 2024

IET Power Electronics

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A type‐2 fuzzy logic‐based adaptive backstepping control (T2FABSC) approach is designed for an H‐bridge inverter. This inverter has an LC filter to decrease the level of total harmonic distortion (THD) that can affect the efficiency of the system. Reduction of THD and stability insurance of the filter are challenging trade‐offs, tackled here by a controller design. The performance, however, is not suitable for actual applications under a wider range of disturbances, and the parameters need to be adjusted once more for more dependable operations. Backstepping control is given a Lyapunov definition‐based adaptive mechanism that can improve this scheme's stability and robustness in the face of numerous disturbances. Additionally, the system is viewed as a “Black box” without the need for a precise mathematical model, which might lead to a lighter computing burden and simpler implementation. Moreover, a fuzzy type‐2 structure is adopted that can optimize the gains of the adaptive Backstepping controller (ABSC) in challenging conditions. The antlion optimization algorithm is employed to optimize the parameters of the membership functions in the fuzzy system, hence improving the performance of the controller. In addition, compared with different optimization algorithms, it can more quickly and accurately locate the best solutions. Finally, the findings of both the simulations and the experimental outputs are examined, proving the T2FABSC's significant robustness and faster dynamics in a variety of challenging circumstances.

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Section: State Augmented Adaptive Backstepping Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust adaptive backstepping control of H‐bridge inverter based on type‐2 fuzzy optimization of parameters

Azarinfar,

Khosravi,

Soroush

et al. 2024

IET Power Electronics

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“…A fifth-order DFIM that incorporates both the electrical and mechanical dynamic is provided as [13], [17] based on the suppositions of a linear magnetic circuit and equal mutual inductance.…”

Section: Doubly-fed Induction Motor Modelmentioning

confidence: 99%

“…As a result, the experiences of the operators of a technical process can be taken into account. One of the most often utilized methods for strengthening control, resilience against parametric and nonparametric variation is fuzzy logic [16], [17].…”

Section: Introductionmentioning

confidence: 99%

Speed control of doubly fed induction motor using backstepping control with interval type-2 fuzzy controller

Herizi¹,

Rouabhi²,

Abderrahim³

2023

Diagnostyka

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The control of the doubly-fed induction motor is a complex operation because of this motor characterised by a non-linear multivariable dynamics, having settings that change over time and a significant link between the mechanical component and magnetic behavior (flux) (speed and couple). This article then proposes a new strategy of a robust control of this motor, which is decoupled due to the stator flux's direction. The proposed control is integrated with the backstepping control which based on Lyapunov theory; this approach consists in constructively designing a control law of nonlinear systems by considering some state variables as being virtual commands, and the important branch of artificial intelligence type-2 fuzzy logic. The hybrid control backstepping-fuzzy logic consists in replacing the regulators applied to the backstepping control by regulators based on type-2 fuzzy logic. This control will be evaluated by numerous simulations where there is a parametric and non-parametric variation.

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“…The suggested approach is based on the combination of backstepping (Bodó and Lantos, 2019;Dashkovskiy and Pavlichkov, 2018;Haouari et al, 2020;Yu et al, 2018) and the RST controller (Ali et al, 2016;Brahim et al, 2017;Jiang et al, 2018;Khadraoui et al, 2014) to attain high performance against the occurred faults. The stability of the closed-loop system of the proposed controller is demonstrated based on the Lyapunov theory (Elmahfoud et al, 2020;Herizi and Barkat, 2019;Mohamed et al, 2020). Simulation results have shown the effectiveness and superiority of our proposed control law.…”

Section: Introductionmentioning

confidence: 96%

Enhanced Reliability for Winding Machine via New Fault Tolerant Control Based on RST-Backstepping Controller

Haouari¹,

Messekher²,

Bali

et al. 2021

Power Electronics and Drives

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Due to the external disturbances, model uncertainties, strong coupling, and occurred faults, the winding machine presents a great control challenge. In order to deal with these problems, this paper presents the formulation of a novel scheme of fault tolerant control (FTC) for three-motor web-winding systems; it is concerned with the nonlinear robust backstepping control based on the combination of RST and backstepping controllers where the process is modelled by a nonlinear model. The main contribution of the paper is that the approach developed here summarises the performance of RST and backstepping controllers in order to design a robust controller capable of eliminating external disturbances and sensor faults affecting the system. The stability of the whole system is proven using the Lyapunov theory. Finally, analysis in comparison with the conventional backstepping controller and simulations in the MATLAB environment are accomplished to confirm the efficiency of the proposed method.

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Backstepping Control Associated to Modified Space Vector Modulation for Quasi Z-source Inverter Fed by a PEMFC

Cited by 3 publications

References 15 publications

Robust adaptive backstepping control of H‐bridge inverter based on type‐2 fuzzy optimization of parameters

Robust adaptive backstepping control of H‐bridge inverter based on type‐2 fuzzy optimization of parameters

Speed control of doubly fed induction motor using backstepping control with interval type-2 fuzzy controller

Enhanced Reliability for Winding Machine via New Fault Tolerant Control Based on RST-Backstepping Controller

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