Reduced-Order Backstepping Controller for POESLL DC–DC Converter Based on Pulse Width Modulation

Abjadi, Navid Reza; Goudarzian, Alireza; Markadeh, Gholamreza Arab; Valipour, Z.

doi:10.1007/s40998-018-0096-y

Cited by 13 publications

(8 citation statements)

References 10 publications

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“…Super lift Luo converter topologies that were introduced by Luo and He, 26 has high voltage gain and better switch utilization compared with classical converters, resulting in less switching losses and high efficiency of POESLLC. 27 The output voltage of these topologies increases with geometric progression contrary to arithmetic progression. These converters are divided into two series as positive and negative according to the output voltage polarity.…”

Section: Super Lift Luo Convertermentioning

confidence: 99%

Design of type‐2 fuzzy logic controller optimized with firefly algorithm for maximum power point tracking of photovoltaic system based on super lift Luo converter

Keçecioğlu

2022

Int J Numerical Modelling

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The efficiency is a very important parameter for photovoltaic systems. Positive output elementary super lift Luo converter classified as high gain DC‐DC converter are used in photovoltaic systems because of their advantages such as high efficiency, reduced ripples, and low switching loss. The drawback of the photovoltaic system based on this converter is its sensitivity to small changes on the control signal. Both maximum power point tracking and control signal stability require a powerful control system as this is a challenging task for the photovoltaic system. Interval type‐2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainties better than type‐1 fuzzy logic systems. In this work, interval type‐2 Takagi–Sugeno–Kang fuzzy logic controller was first designed as a controller. Then, the controller, which was proposed for this paper, was optimized with the Firefly Algorithm to improve the control performance. Performance of controllers is evaluated via comparative simulation studies under the most demanding environmental conditions. It has been observed that the proposed controller reduces the settling time by more than 50% and increases the efficiency up to 10% according to the simulation situations.

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Section: Super Lift Luo Convertermentioning

confidence: 99%

Design of type‐2 fuzzy logic controller optimized with firefly algorithm for maximum power point tracking of photovoltaic system based on super lift Luo converter

Keçecioğlu

2022

Int J Numerical Modelling

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“…During the switch closed period, the voltage across capacitor C 1 is charged with V PV , and the current i L increases with V PV through inductor L . However, the current i L decreases with ( V out – 2 V PV ) throughout the switch open period 21 . Supposing that the POESLLC operates at an efficiency rate of 100% with a resistive load R L , the power generated the PV panel can be calculated as follows:

P_{PV} = {[(\frac{2 - D}{1 - D}) V_{italicPV}]}^{2} \frac{1}{R_{L}} .

…”

Section: Photovoltaic Generation Systemmentioning

confidence: 99%

Improving dynamic efficiency of photovoltaic generation systems using adaptive type 2 fuzzy‐neural network via EN 50530 test procedure

Ganı

2021

Circuit Theory & Apps

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In recent years, photovoltaic generation systems (PGSs) have been fairly popular thanks to the methods proposed for the improvement of the dynamic efficiency. For a more accurate evaluation of the actual dynamic performance in PGSs, a dynamic maximum power point tracking (MPPT) efficiency test based upon an international test procedure such as the European Procedure EN 50530 is of vital importance. The varying gradient irradiance profile in EN 50530 test procedure causes uncertainties in PGSs, which lead to unstable operating conditions for PGSs. It is a challenging task to provide stable operation for PGSs. To overcome this problem, an effective MPPT method based upon adaptive type 2 fuzzy‐neural network (AT2FNN) is proposed using EN 50530 test procedure specifically designed for the dynamic performance of PGSs. The dynamic efficiency performance of the proposed method is analyzed using comparative simulation studies with conventional MPPT methods such as perturb and observe (P&O) and incremental conductance (IC) in Matlab/Simulink environment. The average dynamic efficiency of PGSs is used as performance criteria in the present study. The numerical results obtained from comparative simulation studies indicated that the proposed method improved average dynamic efficiency by almost 4.3% and 9.2% compared to IC and P&O MPPT methods, respectively. The average dynamic efficiency performance of PGS was considerably improved by the proposed method.

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“…In addition, it also provides inconsistent switching frequency that begets the problem of electromagnetic interference [21,22]. In some cases, SMC fails to track the output voltage and hence, it shows steady-state error [23].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis Between Dmrac and Pi Control Algorithms for Dc-dc Converter of Hybrid Energy Storage System in Electric Vehicle

Islam

Abdullah

Farhana

et al. 2022

Preprint

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This paper presents a performance comparison between Direct Model Reference Adaptive Control (DMRAC) with the conventional Proportional Integral (PI) control for the Hybrid Electric Vehicle (HEV) power converter. It is well noted that the power converter of HEV is highly nonlinear due to the load demand variation and duty ratio changes in different driving modes. To cope with this issue, the nonlinear control approach of DMRAC is proposed as an alternative to the conventional linear PI control algorithm. The prime focus is to regulate the power distribution in the power converter system to track the load and current demand by the HEV. MATLAB Simulink toolbox is used to construct the system and simulate the responses of the two controllers. For regular operation, the results show that DMRAC outperform PI controller in tracking both current and load demands. While in the presence of disturbance, DMRAC can only show its efficacy in current demand tracking and requires some time to surpass the PI controller in tracking the load demand. The performances have been calculated based on the Root Mean Square Error (RMSE). Based on the finding, it can be proved that the DMRAC can become a good alternative to control the power of HEV through power converters, especially when there is a variation in the demanded current.

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Reduced-Order Backstepping Controller for POESLL DC–DC Converter Based on Pulse Width Modulation

Cited by 13 publications

References 10 publications

Design of type‐2 fuzzy logic controller optimized with firefly algorithm for maximum power point tracking of photovoltaic system based on super lift Luo converter

Design of type‐2 fuzzy logic controller optimized with firefly algorithm for maximum power point tracking of photovoltaic system based on super lift Luo converter

Improving dynamic efficiency of photovoltaic generation systems using adaptive type 2 fuzzy‐neural network via EN 50530 test procedure

Performance Analysis Between Dmrac and Pi Control Algorithms for Dc-dc Converter of Hybrid Energy Storage System in Electric Vehicle

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