Model and design of a fuzzy-based Hopfield NN tracking controller for standalone PV applications

Ramu, Arulmurugan; Suthanthiravanitha, N.

doi:10.1016/j.epsr.2014.05.007

Cited by 49 publications

(12 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Soft computing (SC) methods are also utilized to develop MPPT algorithms suitable for fast changing environments. Among these techniques, particle swarm optimizations (PSO) method together with extension theory (Chao, 2014), conventional fuzzy logic control (FLC) (Messai et al, 2011;Al Nabulsi and Dhaouadi, 2012;Letting et al, 2012;Radjai et al, 2014;Zainuri et al, 2014), asymmetrical FLC (Liu et al, 2014a,b), multi FLC (Rajesh and Mabel, 2014), adaptive FLC (Guenounou et al, 2014), artificial neural network (ANN) (Kulaksiz and Akkaya, 2012) and FLC combined with Hopfield ANN (Arulmurugan and Suthanthiravanitha, 2015) are utilized to obtain the appropriate PS. Moreover, genetic algorithms (Messai et al, 2011;Kulaksiz and Akkaya, 2012) and S-function based PSO (Letting et al, 2012) are used to optimize the parameters of these SC methods.…”

Section: Introductionmentioning

confidence: 99%

A comparative study on maximum power point tracking techniques for photovoltaic generation systems operating under fast changing environments

Chen

Liu

et al. 2015

Solar Energy

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

A comparative study on maximum power point tracking techniques for photovoltaic generation systems operating under fast changing environments

Chen

Liu

et al. 2015

Solar Energy

View full text Add to dashboard Cite

“…The application of artificial intelligence techniques for MPPT such as neural networks [27], [28], intelligent algorithms [29]- [31] and fuzzy logic controllers (FLCs) [32]- [35] has significantly improved the tracking performance under different conditions compared with conventional methods. Unlike linear controllers, the FLCs are intelligent systems that have no sensitivity to the variation of topology, parameters and operation conditions.…”

Section: Introductionmentioning

confidence: 99%

Optimized Fuzzy Controller for MPPT of Grid-connected PV Systems in Rapidly Changing Atmospheric Conditions

Dehghani

Taghipour

Gharehpetian

et al. 2021

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

Due to nonlinear behavior of power production of photovoltaic (PV) systems, it is necessary to apply the maximum power point tracking (MPPT) techniques to generate the maximum power. The conventional MPPT methods do not function properly in rapidly changing atmospheric conditions. In this study, a fuzzy logic controller (FLC) optimized by a combination of particle swarm optimization (PSO) and genetic algorithm (GA) is proposed to obtain the maximum power point (MPP). The proposed FLC uses the ratio of power variations to voltage variations and the derivative of power variations to voltage variations as inputs and uses the duty cycle as the output. The range of changes in fuzzy membership functions and fuzzy rules are proposed as an optimization problem optimized by the PSO-GA. The proposed design is validated for MPPT of a PV system using MATLAB/Simulink software. The results indicate a better performance of the proposed FLC compared to the common methods.

show abstract

“…Although the several researches have been carried out in the area of SPV array fed water pumping, combining various DC-DC converters and motor drives, the zeta converter in association with the permanent magnet brushless DC (BLDC) motor is still unexplored to develop such kind of system. However, the zeta converter has been used in some other SPV based applications [1][2][3][4]. The merits of both the BLDC motor and zeta converter can contribute to develop a favorable SPV array fed water pumping system possessing the potential of operating satisfactorily under the dynamically changing atmospheric conditions.…”

Section: Introductionmentioning

confidence: 99%

BLDC motor driven solar PV array fed water pumping system employing zeta converter

Kumar

Singh

2014

2014 IEEE 6th India International Conference on Power Electronics (IICPE)

View full text Add to dashboard Cite

This paper proposes a solar photovoltaic (SPV) array fed water pumping system utilizing a zeta converter as an intermediate DC-DC converter in order to extract the maximum available power from the SPV array. Controlling the zeta converter in an intelligent manner through the incremental conductance maximum power point tracking (INC-MPPT) algorithm offers the soft starting of the brushless DC (BLDC) motor employed to drive a centrifugal water pump coupled to its shaft. Soft starting i.e. the reduced current starting inhibits the harmful effect of the high starting current on the windings of the BLDC motor. A fundamental frequency switching of the voltage source inverter (VSI) is accomplished by the electronic commutation of the BLDC motor, thereby avoiding the VSI losses occurred owing to the high frequency switching. A new design approach for the low valued DC link capacitor of VSI is proposed. The proposed water pumping system is designed and modeled such that the performance is not affected even under the dynamic conditions. Suitability of the proposed system under dynamic conditions is demonstrated by the simulation results using MATLAB/Simulink software.

show abstract

Model and design of a fuzzy-based Hopfield NN tracking controller for standalone PV applications

Cited by 49 publications

References 17 publications

A comparative study on maximum power point tracking techniques for photovoltaic generation systems operating under fast changing environments

A comparative study on maximum power point tracking techniques for photovoltaic generation systems operating under fast changing environments

Optimized Fuzzy Controller for MPPT of Grid-connected PV Systems in Rapidly Changing Atmospheric Conditions

BLDC motor driven solar PV array fed water pumping system employing zeta converter

Contact Info

Product

Resources

About