Fuzzy control for maximum power-point tracking of a photovoltaic system

Safia, Zeineb Ben; Allouch, M.; Harrabi, Naziha; Bahloul, Mohamed; Chaabane, Mohamed; Aïtouche, Abdel

doi:10.1109/icosc.2018.8587824

Cited by 1 publication

(7 citation statements)

References 13 publications

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“…Then, we will present the equations from the PV panel and the DC-DC boost converter's functioning. The PV panel equations are related to the DC-DC boost converter by a T-S fuzzy model were obtained from [31,32], which describes the PV system.…”

Section: T-s Fuzzy Model For the Pv Systemmentioning

confidence: 99%

“…A PV cell is a system that converts light into electricity through the photoelectric effect. A PV cell is generally represented by an equivalent circuit [31,32] shown in Figure 1.…”

Section: Pv System Modelmentioning

confidence: 99%

“…where V T is the thermal voltage, V pv is the photovoltaic output voltage, R s is the shunt resistance, and I s is the saturation current which is represented by [31,32]…”

Section: Pv System Modelmentioning

confidence: 99%

“…In [30], the H ∞ control approach based on a fuzzy proportional-integral (PI) was used as a state feedback control in the control design and stability conditions of the closed-loop PV system. In [31], the boost converter was controlled using the T-S fuzzy parallel distributed compensation (PDC) to ensure stability and zero tracking error. To achieve MPPT under varying climatic conditions, the authors in [32] propose an H ∞ observer-based fuzzy controller.…”

Section: Introductionmentioning

confidence: 99%

“…The first rule base is intended for adjusting the boost converter's duty cycle, while the second rule base is designed for online adjusting of the controller's gain. It is worth noting that the techniques proposed in [29][30][31][32] compute their controller gains offline. Theoretically, the above methods ensure good efficiency, fast PV power convergence to the MPPT, and a smoother steady-state response without oscillation around the MPPT.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Takagi–Sugeno State Delayed Feedback and Integral Control for PV Systems: Modeling, Simulation, and Control

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Barbosa

Chávez

et al. 2021

International Journal of Photoenergy

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The integration of the large-scale photovoltaic systems has experienced significant growth, which is similarly expected to occur with small-scale photovoltaic systems. Since small-scale systems must be simple in cost-effective components, control strategies must be implemented in low complexity circuits. However, current maximum power point tracking (MPPT) algorithms are generally complex and require electronic components to support variable control gains for different irradiance conditions, preventing simple MPPT implementations suitable for small-scale photovoltaic systems. This paper proposes a new control strategy to tackle the power tracking problem of the power systems. First, a dynamic model of the photovoltaic system is described and converted into a Takagi–Sugeno (T-S) model. Then, an MPPT scheme is proposed in series with a fixed integral and a fuzzy gain state delay feedback controller, which avoids the need for a variable control gain, simplifying the electronic implementation of the control strategy. New delay-dependent stabilization conditions based on the Lyapunov-Krasovskii functional are proposed in terms of a convex optimization problem, where the delayed feedback and integral gains are designed simultaneously. Simulation results using Matlab and Simulink are used to validate the proposed method.

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Section: T-s Fuzzy Model For the Pv Systemmentioning

confidence: 99%

“…A PV cell is a system that converts light into electricity through the photoelectric effect. A PV cell is generally represented by an equivalent circuit [31,32] shown in Figure 1.…”

Section: Pv System Modelmentioning

confidence: 99%

“…where V T is the thermal voltage, V pv is the photovoltaic output voltage, R s is the shunt resistance, and I s is the saturation current which is represented by [31,32]…”

Section: Pv System Modelmentioning

confidence: 99%