The significant progress in robotics worldwide, brings further advancements in the design of the mechanical components, miniaturization of sensors and control hardware and more sophisticated control algorithms that come together with more available processing power. The state of the art humanoid robots are usually equipped with dexterous hands. This paper presents the design of the FTN robot hand for humanoid robot MARKO, with the emphasis on the fuzzy logic controller to control the Brushed DC motors used to actuate the underactuated fingers of the hand. The design of the robotic hand is highly anthropomorphic and biologically inspired by the human hands. The hand is passively adaptive to the shape of an object, due to a tendon-driven mechanism and torsional spring in each finger joint. Each of the five fingers has three DOFs (Degrees Of Freedom), except the thumb which has an additional DOF, for the rotation in its base. The fingers are tendon-driven, actuated with five DC motors, embedded in the palm. The proposed fuzzy controller is used to control the position of each finger. The results of the controller are compared with traditional PID control algorithms tuned with Ziegler-Nichols tuning method. The algorithms are first developed in a simulation environment and later are implemented on a real-time ARM Cortex M4 controller.
In this age of depleting fossil fuels, more emphasis has to be placed on the renewable sources of energy. People are conscious about a clean and pollution free environment and thus a primary candidate in this respect would be solar energy. In this paper the maximum power point of a PV system is tracked using a fuzzy logic controller. The advantages of a fuzzy logic controller are that it is robust, doesn't require the exact knowledge of the model and is relatively simple to design. Using an FLC (fuzzy logic controller) is considered as an intelligent method of maximum power point tracking.
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