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This work explains the comparison of various dc-dc converters for photovoltaic systems. In recent day insufficient energy and continues increasing in fuel cost, exploration on renewable energy system becomes more essential. For high and medium power applications, high input source from renewable systems like photovoltaic and wind energy system turn into difficult one, which leads to increase of cost for installation process. So the generated voltage from PV system is boosted with help various boost converter depends on the applications. Here the various converters are like boost converter, buck converter, buck-boost converter, cuk converter, sepic converter and zeta converter are analysed for photovoltaic system, which are verified using matlab / simulink.

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Summary In this paper, a fuzzy logic–based jamming detection algorithm (FLJDA) is proposed to detect the presence of jamming in downstream data communication for cluster‐based wireless sensor networks. The proposed FLJDA keeps an eye on the existing nodes and new node to determine their behavior by applying fuzzy logic on measured jamming detection metrics. To monitor the behavior of the nodes, the FLJDA computes the jamming detection metrics, namely, packet delivery ratio and received signal strength indicator. The major features of this paper are the following: (1) The jamming detection algorithm is specifically implemented for downstream data communication, (2) cluster head estimates jamming detection metrics for detecting the jamming unlike the existing algorithms where individual nodes explicitly collect the jamming detection metrics, and (3) the proposed algorithm optimizes the jamming detection metrics on the basis of fuzzy logic unlike the existing approaches, which uses merely jamming detection threshold alone for jamming detection. The simulation results of the proposed system provide the true detection ratio as high as 99.89%.