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Automation has been growing in recent years for the manufacturing industries to increase productivity. Multiple robotic arms are used to handle materials for lifting in flexible directions. The vertical rotation of a 360 degree single arm is considered in this research on a position servo drive with brushless DC motor. The load torque of an arm varies depending upon the angular displacement due to gravity, so it requires four-quadrant operation of the drive with a robust feedback controller. This paper deals with the design and performance comparison of a conventional PID feedback controller with a fuzzy-based PID controller and suggests the most suitable controller. The design was implemented in real time through the dSPACE DS1104 controller environment to verify the dynamic behaviors of the arm.

Among other soft computing techniques, the Adaptive Neuro Fuzzy Inference System (Anfis) gives a significant and advantageous result in solar power generation, especially in tracking the maximum power point. Due to the dynamic nature of solar irradiance and temperature, efficient energy conversion is not possible. However, advancements in the areas of artificial intelligence have made it possible to overcome the hurdles. The Maximum Power Point Tracking (MPPT) technique adopting the advantages of Anfis has been proven to be more successful with a fast dynamic response and high accuracy. The complete system is modeled using Matlab/Simulink; the hardware results are validated with the benefits of Field Programmable Logic Array (FPGA) instead of ordinary micro-controllers.