In this paper guides in the fuzzy logic and Neural network variable step size Incremental conductance maximum power point tracking controller were analyzed as well suggested on further work. Firstly, the Fuzzy Logic Control (FLC) controller based hardware system derived paper were discussed followed by Neural Network (NN) based VSS Inc-Cond were discussed in the second half. In the first paper derived simple FLC I.e short, medium and long distance were considered to derive the 25 rules. The input of FLC are current and voltage, the output of FLC is duty cycle or D. The duty cycle apply into variable step Inc-conductance method to find the optimal point of the PV system. Further discussed experimental block diagram of FLC-Inc-Cond system. At the end of the paper authors compared various hardware to show tabulations. In the second half, initially discussed conventional Inc-Cond, followed by general Fuzzy logic controller were discussed. Further author derived VSS Inc-Cond based NN MPPT were developed on Matlab simulink. The output of FLC-Inc Cond as well NN based MPPT is great performance when compare to conventional system.

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Resonant converters are very attractive in practice because they have high efficiency, small size, light weight, fast dynamic response, low component stresses and low noise. One of the relatively new resonant DC-DC converters is a Series-Parallel Resonant Converter (SPRC) also called an LCC converter. Under constant frequency, the filter designs are simplified and utilization of magnetic components is improved. The LCC-SPRC takes on the desirable characteristics of the pure series and the pure parallel converter, thus removing the main disadvantages. The use of soft-switching techniques alleviates switching loss problems and allows a significant increase in the converter switching frequency. In the present work Bi-directional Series Parallel Resonant Converter are designed and the simulation results are presented.