Multiobjective maximum power tracking control of photovoltaic systems: T-S fuzzy model-based approach

Allouche, Moez; Dahech, Karim; Chaabane, Mohamed

doi:10.1007/s00500-017-2691-7

Cited by 24 publications

(21 citation statements)

References 23 publications

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“…A dc-dc boost converter is connected to the PV array to adjust the PV array power, as shown in Figure 1. The dynamic model of the converter can be defined by state space equations (Allouche et al, 2018), where the panel voltage V pv ( t ) , the inductor current i L ( t ) and the load voltage V 0 ( t ) are taken as state variables, as follows:…”

Section: Fuzzy Modelling Of Pv Generator Systemsmentioning

confidence: 99%

H_∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

Houda¹,

Saifia

Chadli

et al. 2020

Transactions of the Institute of Measurement and Control

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This paper presents a new strategy for a robust maximum power point (MPP) tracking fuzzy controller for photovoltaic (PV) systems subject to actuator asymmetric saturation. A DC-DC boost converter is used to connect a PV panel with an output load. The output voltage of the DC-DC boost converter can be adjusted by duty ratio that is limited between 0 and 1. The aim of our control design is to track the MPP under atmospheric condition changes and the presence of the asymmetric saturation of the duty ratio. To minimize tracking error and disturbance effect, the dynamic behaviour of a PV system and its reference model are described by using Takagi–Sugeno fuzzy models. Then, a constrained control based on a fuzzy PI state feedback controller is proposed. The H∞ control approach is used in control design and stability conditions of the closed-loop system are formulated and solved in terms of linear matrix inequalities. Finally, simulation results are given to show the tracking performance of the control design.

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Section: Fuzzy Modelling Of Pv Generator Systemsmentioning

confidence: 99%

H_∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

Houda¹,

Saifia

Chadli

et al. 2020

Transactions of the Institute of Measurement and Control

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“…To determine the desired trajectory to be tracked by the PV system, a reference model is elaborated using the optimal P‐V current and voltage ( I pvopt and V pvopt ) characteristic. Therefore, the state space representation of the reference model, which gives the MPP value, is writing as :

{\overset{x}{true}}_{d} ((), t) = A_{d} ((), z ((), t)) x_{d} ((), t) + r ((), t)

with:

A_{d} = ([], \begin{matrix} center center center \\ array - \frac{(R_{L} + R_{b} I_{b})}{L} & array \frac{d_{o p t}}{L} & array - \frac{1}{L} \\ array - \frac{d_{o p t}}{C_{a}} & array 0 & array 0 \\ array \frac{I_{b}}{C_{a}} & array 0 & array 0 \end{matrix}), r ((), t) = ([], \begin{matrix} center \\ array - \frac{(d_{o p t} - 1) v_{d}}{L} \\ array \frac{I_{p v o p t}}{C_{a}} \\ array 0 \end{matrix})

…”

Section: H∞ Switching Fuzzy Tracking Mppt Constrained Controlmentioning

confidence: 99%

“…To determine the desired trajectory to be tracked by the PV system, a reference model is elaborated using the optimal P-V current and voltage (I pvopt and V pvopt ) characteristic. Therefore, the state space representation of the reference model, which gives the MPP value, is writing as [23]:…”

Section: Reference Modelmentioning

confidence: 99%

“…The switched fuzzy system has been taken its place in the development of the control methods based on T‐S systems , especially in the case of actuator saturation, where the asymmetric saturation is represented by a switching algorithm . Using T–S fuzzy models, several authors have proposed MPPT control of PV systems using DC‐DC converters to adjust the PV input voltage in recent year. However, in the aforementioned papers, the authors have not considered the asymmetric saturation of duty ratio

((), d ((), t))

which is subject to saturation between 0 and 1

((), d ((), t) \in ([], \begin{matrix} center center \\ array 0 & array 1 \end{matrix}))

.…”

Section: Introductionmentioning

confidence: 99%

“…On other hand, the H ∞ performance criterion has been utilized to ensure disturbances effects attenuation in many control applications . In particular, a T–S reference model tracking control of nonlinear dynamic PV systems using boost converter via H ∞ performance has been proposed in . However, for the best of our knowledge, the H ∞ tracking control based on T–S reference model has been never applied to the PV systems in the presence of asymmetric actuators saturation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

H∞ switching fuzzy control of solar power generation systems with asymmetric input constraint

Nasri

Saifia

Chadli

et al. 2019

Asian Journal of Control

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This paper aims at presenting a maximum power point tracking (MPPT) controller for photovoltaic (PV) systems subject to asymmetric input constraint.Indeed, the output voltage of the DC-DC converter used for adjusting the photovoltaic output power can be controlled by means of variation of duty ratio limited between 1 and 0. The control design goal is to improve the efficiency of PV systems under asymmetric saturation of duty ratio. To achieve this goal, first, a Takagi-Sugeno (T-S) fuzzy model is used to represent the nonlinear behavior of the PV system. A T-S reference model is employed to give the ideal state direction which must be followed. To achieve a good steady state tracking, the integral of the state tracking error is used to define an extended system state vector. Second, the input characteristic is partitioned into several regions. In each region, the asymmetric saturation function can be considered as a symmetric saturation function. Furthermore, H∞ stabilization conditions for the resulting switching fuzzy control of the PV system under actuator saturation are formulated in term of linear matrix inequalities (LMI) using the Lyapunov approach. Simulation results are exhibited to demonstrate the effectiveness of the proposed design method.

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SOS-Based Robust Control Design Subject to Actuator Saturation for Maximum Power Point Tracking of Photovoltaic System

Boubekri

Saifia

Doudou

et al. 2023

Studies in Systems, Decision and Control

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Multiobjective maximum power tracking control of photovoltaic systems: T-S fuzzy model-based approach

Cited by 24 publications

References 23 publications

H_∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

H_∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

H∞ switching fuzzy control of solar power generation systems with asymmetric input constraint

SOS-Based Robust Control Design Subject to Actuator Saturation for Maximum Power Point Tracking of Photovoltaic System

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Multiobjective maximum power tracking control of photovoltaic systems: T-S fuzzy model-based approach

Cited by 24 publications

References 23 publications

H∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

H∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

H∞ switching fuzzy control of solar power generation systems with asymmetric input constraint

SOS-Based Robust Control Design Subject to Actuator Saturation for Maximum Power Point Tracking of Photovoltaic System

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H_∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints

H_∞ fuzzy proportional integral state feedback controller of photovoltaic systems under asymmetric actuator constraints