A Multilevel Inverter for Photovoltaic Systems With Fuzzy Logic Control

Cecati, Carlo; Ciancetta, Fabrizio; Siano, Pierluigi

doi:10.1109/tie.2010.2044119

Cited by 378 publications

(137 citation statements)

References 37 publications

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“…In this method reference signal is compared with Pulse width Modulation output and then error signal will produce [11].…”

Section: Fig (4)fuzzy Logic Controller Block Diagrammentioning

confidence: 99%

“…For DC-DC converter we will use MPPT control technique for stabilizingDC [8] voltage and for Multilevel inverter we will use any of the PWM control techniques along with PI controller etc. By using this methods we can't achieve Reactive power compensation and design of PV system wise also some problems are there like leakage current etc [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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Active & Reactive power Control of Large scale Grid Connected PV system by Cascaded Modular Multi-Level Inverters withFuzzy Logic Control Approach

2017

IJMTER

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Abstract-Due to its advantages like clean energy production and more abundance availability solar energy is the most concentrated topic from last 20 years. Grid connected PV system gaining its importance due to high demand of power across the globe. Now a days different topologies of Multilevel Inverters are developing. By using this multilevel inverters we can interface the PV systems with Grid easily and effectively. But PV system facing so many problems like power flow control and output voltage disturbances because PV systems produce irregular output voltages. This paper demonstrates the Cascade Multilevel inverter with Active and Reactive power control using Fuzzy logic control approach of for Grid Connected PV System. With the help of this model we can improve the performance of the total PV system. In this paper we proposed a 3-MW, 12-kV PV system with the Fuzzy Logic control strategy is modelled and simulated in MATLAB.

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“…In this method reference signal is compared with Pulse width Modulation output and then error signal will produce [11].…”

Section: Fig (4)fuzzy Logic Controller Block Diagrammentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Active & Reactive power Control of Large scale Grid Connected PV system by Cascaded Modular Multi-Level Inverters withFuzzy Logic Control Approach

2017

IJMTER

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“…To give a solution for the formation problem, formation error is de�ned as (26) and the control law is designed based on (29), where and . Figure 3(a) shows the formation trajectory of six robots starting from initial conditions (Table 2) to the �nal unit hexagon (57) in 30 secs and Figure 3(b) shows the potential value.…”

Section: Example I (Six Agents With Known Dynamicsmentioning

confidence: 99%

“…Since Zadeh [26] initiated the fuzzy set theory, fuzzy logic systems (FLS) have been widely applied to many real world applications [27][28][29][30]. However, fuzzy control has not been viewed as a rigorous science due to a lack of formal synthesis techniques which guarantee the very basic requirements of global stability and acceptable performance.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive -Based Formation Control for Multirobot Systems

2013

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We describe a decentralized formation problem for multiple robots, where an ∞ formation controller is proposed. e network of dynamic agents with external disturbances and uncertainties are discussed in formation problems. We �rst describe how to design social potential �elds to obtain a formation with the shape of a polygon. en, we provide a formal proof of the asymptotic stability of the system, based on the de�nition of a proper Lyapunov function and ∞ technique. e advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, while applicability on a group of any autonomous systems with -degrees of freedom. Finally, simulation results are demonstrated for a multiagent formation problem of a group of six robots, illustrating the effective attenuation of approximation error and external disturbances, even in the case of agent failure or leader tracking.

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“…Multilevel inverters are designed based on configuration of more switches and DC supplies to achieve the goal of generating various voltage levels at the output. Such inverters generate low harmonic waveforms; therefore they are most suitable for energy conversion applications to deliver efficient power to the loads from renewable energy sources like photovoltaic systems [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%