Fuzzy Controller for Matrix Converter System to Improve its Quality of Output

In this paper, Fuzzy Logic controller is developed for ac/ac Matrix Converter. Furthermore, Total Harmonic Distortion is reduced significantly. Space Vector Algorithm is a method to improve power quality of the converter output. But its quality is limited to 86.7%.We are introduced a Cross coupled DQ axis controller to improve power quality. The Matrix Converter is an attractive topology for High voltage transformation ratio. A Matlab / Simulink simulation analysis of the Matrix Converter system is provided. The design and implementation of fuzzy controlled Matrix Converter is described. This AC-AC system is proposed as an effective replacement for the conventional AC-DC-AC system which employs a two-step power conversion.Comment: 11 page

Genetic algorithm based adaptive offloading for improving IoT device communication efficiency

Improving the communication of Internet of Things (IoT) network is a challenging task as it connects a wide-range of heterogeneous mobile devices. With an extended support from cloud network, the mobile IoT devices demand flexibility and scalability in communication. Increase in density of communicating devices and user request, traffic handling and delay-less service are unenviable. This manuscript introduces genetic algorithm based adaptive offloading (GA-OA) for effective traffic handling in IoT-infrastructure-cloud environment. The process of offloading is designed to mitigate unnecessary delays in request process and to improve the success rate of the IoT requests. The fitness process of GA is distributed among the gateways and infrastructure to handle requests satisfying different communication metrics. The process of GA balances between the optimal and sub-optimal solutions generated to improve the rate of request response. Experimental results prove the consistency of the proposed GA-OA by improving request success ratio, achieving lesser complexity, delay and processing time