Decentralized T-S Fuzzy Control for Solar PV Powered Water Pumping System Driving by Induction Motor

Safia, Zeineb Ben; Allouch, M.; Chaabane, Mohamed

doi:10.18280/ejee.224-502

Cited by 3 publications

(5 citation statements)

References 16 publications

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“…The boost converter's dynamics can be described by an average model, which assembles the two sets of equations that correspond to the switch's “ON” and “OFF” states, as shown in Reference 26. As a result, we get the state space equation below:

{\dot{x}}_{1} (t) = A_{2}^{1} x_{1} (t) + B^{1} x_{1} (t) u_{1} (t) + E_{1} w_{1} (t),

where,

u_{1} (t) \in [0, 1]

is the duty cycle to command the switch of the boost converter and

𝒜_{2}^{1}

presents the state matrix corresponding to “OFF” state of the switch.…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Also, we used the same principal as a standard PDC controller, but in addition, we took into consideration the tracking error's expression:

e_{1} (t) = (x_{1} (t) - x_{1 r} (t))

which must converge to zero so that we guarantee the operation at the MPP. Here is below the TS fuzzy model of the DC/DC converter: 26

{\dot{x}}_{1} (t) = \sum_{i = 1}^{4} h_{i} (z_{1} (t)) (A_{2}^{1} x_{1} (t) + B_{i}^{1} u_{1} (t) + E_{1} w_{1} (t)),

h_{i} (z_{1} (t)) = \frac{λ_{i} false(z_{1} false(t false) false)}{\sum_{i = 1}^{8} λ_{i} false(z_{1} false(t false) false)}; λ_{i} (z_{1} (t)) = \prod_{k = 1}^{2} F_{i, k} (z_{1 k} (t)); h_{i} (z (...

…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Here is below the TS fuzzy model of the DC/DC converter: 26

{\dot{x}}_{1} (t) = \sum_{i = 1}^{4} h_{i} (z_{1} (t)) (A_{2}^{1} x_{1} (t) + B_{i}^{1} u_{1} (t) + E_{1} w_{1} (t)),

h_{i} (z_{1} (t)) = \frac{λ_{i} false(z_{1} false(t false) false)}{\sum_{i = 1}^{8} λ_{i} false(z_{1} false(t false) false)}; λ_{i} (z_{1} (t)) = \prod_{k = 1}^{2} F_{i, k} (z_{1 k} (t)); h_{i} (z (t)) > 0; \sum_{i = 1}^{4} λ_{i} (z (t)) = 1 .

Concerning the TS fuzzy reference model, it is conceived to specify the optimal states to be tracked

x_{1 r}

, to ensure an optimal operating ...…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Thus, we present the TS fuzzy reference model as in Reference 26 by:

{\dot{x}}_{r 1} (t) = \sum_{k = 1}^{2} h_{r k} (z_{r 1} (t)) (A_{r k}^{1} x_{r 1} (t) + r_{1} (t)) .

As a result, the trajectory tracking problem is transformed into the following tracking error feedback control law as:

u_{1} (t) = \sum_{i = 1}^{4} h_{i} (z_{1} (t)) K_{i}^{1} (x_{1} (t) - x_{r 1} (t)),

where,

K_{i}^{1}

are the controller gains to calculate.…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Remark The design of both TS fuzzy reference model and controller, also the LMIs formulation are more detailed in Reference 26, it is recommended to refer back to it.…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

See 4 more Smart Citations

Renewable energy management of an hybrid water pumping system (photovoltaic/wind/battery) based on Takagi–Sugeno fuzzy model

Safia

Allouche

Chaabane

2022

Optim Control Appl Methods

Self Cite

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This research work presents an optimal energy management for a hybrid water pumping system driven by a photovoltaic generator (PVG) and a wind turbine. These two renewable energies are used as power generation sources, whereas a battery is added as an energy‐storing system, for the purpose of controlling the power flow and providing a constant load supply. The proposed management system, serve to guarantee the pumping system autonomy in a rural region where's no access to the electrical network. As a result, a maximum power point tracking (MPPT) controller is created based on the fuzzy Takagi–Sugeno (TS) model, ensuring maximum power transfer to the moto‐pump in spite of wind speed and insolation changes. The synthesis of MPPT control law involves TS fuzzy reference models which generate the desired trajectories to track. A supervisor has been developed for energy management and its major purpose is to effectively use the battery to satisfy the power load requirements, and that is by maintaining the state of charge (SOC) to extend the battery's life. Finally, simulation results have been done based on Matlab/Simulink with the aim of validating the efficiency of the proposed energy management supervisor.

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{\dot{x}}_{1} (t) = A_{2}^{1} x_{1} (t) + B^{1} x_{1} (t) u_{1} (t) + E_{1} w_{1} (t),

where,

u_{1} (t) \in [0, 1]

is the duty cycle to command the switch of the boost converter and

𝒜_{2}^{1}

presents the state matrix corresponding to “OFF” state of the switch.…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Also, we used the same principal as a standard PDC controller, but in addition, we took into consideration the tracking error's expression:

e_{1} (t) = (x_{1} (t) - x_{1 r} (t))

which must converge to zero so that we guarantee the operation at the MPP. Here is below the TS fuzzy model of the DC/DC converter: 26

{\dot{x}}_{1} (t) = \sum_{i = 1}^{4} h_{i} (z_{1} (t)) (A_{2}^{1} x_{1} (t) + B_{i}^{1} u_{1} (t) + E_{1} w_{1} (t)),

h_{i} (z_{1} (t)) = \frac{λ_{i} false(z_{1} false(t false) false)}{\sum_{i = 1}^{8} λ_{i} false(z_{1} false(t false) false)}; λ_{i} (z_{1} (t)) = \prod_{k = 1}^{2} F_{i, k} (z_{1 k} (t)); h_{i} (z (...

…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Here is below the TS fuzzy model of the DC/DC converter: 26

{\dot{x}}_{1} (t) = \sum_{i = 1}^{4} h_{i} (z_{1} (t)) (A_{2}^{1} x_{1} (t) + B_{i}^{1} u_{1} (t) + E_{1} w_{1} (t)),

h_{i} (z_{1} (t)) = \frac{λ_{i} false(z_{1} false(t false) false)}{\sum_{i = 1}^{8} λ_{i} false(z_{1} false(t false) false)}; λ_{i} (z_{1} (t)) = \prod_{k = 1}^{2} F_{i, k} (z_{1 k} (t)); h_{i} (z (t)) > 0; \sum_{i = 1}^{4} λ_{i} (z (t)) = 1 .

Concerning the TS fuzzy reference model, it is conceived to specify the optimal states to be tracked

x_{1 r}

, to ensure an optimal operating ...…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Thus, we present the TS fuzzy reference model as in Reference 26 by:

{\dot{x}}_{r 1} (t) = \sum_{k = 1}^{2} h_{r k} (z_{r 1} (t)) (A_{r k}^{1} x_{r 1} (t) + r_{1} (t)) .

As a result, the trajectory tracking problem is transformed into the following tracking error feedback control law as:

u_{1} (t) = \sum_{i = 1}^{4} h_{i} (z_{1} (t)) K_{i}^{1} (x_{1} (t) - x_{r 1} (t)),

where,

K_{i}^{1}

are the controller gains to calculate.…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

“…Remark The design of both TS fuzzy reference model and controller, also the LMIs formulation are more detailed in Reference 26, it is recommended to refer back to it.…”

Section: Description and Modeling Of The Suggested Hybrid Water Pumpi...mentioning

confidence: 99%

See 3 more Smart Citations

Renewable energy management of an hybrid water pumping system (photovoltaic/wind/battery) based on Takagi–Sugeno fuzzy model

Safia

Allouche

Chaabane

2022

Optim Control Appl Methods

Self Cite

View full text Add to dashboard Cite

show abstract

A Deep Learning Approach for MPPT of PV System: Design and Comparison

Abulaila,

Alsudi,

Al-Aubidy

2024

2024 21st International Multi-Conference on Systems, Signals &Amp;amp; Devices (SSD)

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Fuzzy Observer Design for PV Conversion System with Fault Effects

Ngo

Truong

2022

JTE

View full text Add to dashboard Cite

This paper proposes a new approach to design an observer for the Photovoltaic conversion system. Originally, the PV conversion system is modeled under the nonlinear framework that is difficult for designing the observer. Thus, in this work, the original nonlinear form of the PV conversion system will be transformed to the T-S fuzzy model with the existence of the disturbance. Unlike the previous articles, the PV conversion system in this work is affected by the faults, and the fault impacts not only the system but also the output. The observer is designed to estimate the unknown states and the faults of the PV conversion system asymptotically as well as eliminate the impact of the disturbance. The augment technique is employed to modify the PV conversion system. With the aid of the Lyapunov theory and Linear Matrix Inequality (LMI) technique, the conditions for observer design have been proposed in the main theorem. Finally, the simulation results are also provided to prove the success and merit of the proposed method.

show abstract

Decentralized T-S Fuzzy Control for Solar PV Powered Water Pumping System Driving by Induction Motor

Cited by 3 publications

References 16 publications

Renewable energy management of an hybrid water pumping system (photovoltaic/wind/battery) based on Takagi–Sugeno fuzzy model

Renewable energy management of an hybrid water pumping system (photovoltaic/wind/battery) based on Takagi–Sugeno fuzzy model

A Deep Learning Approach for MPPT of PV System: Design and Comparison

Fuzzy Observer Design for PV Conversion System with Fault Effects

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