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A fuzzy model reference
adaptive controller for regulating the fabric's tensional forces applied
by a robot during the sewing task is developed. The adaptive fuzzy
logic controller closes the loop outside the internal scara robot
controller. The robot guides a piece of fabric in a conventional
industrial sewing machine while its controller maintains a desired
constant tensional force applied to the fabric during the sewing
process. In each loop, the proposed controller calculates the
appropriate robot end-effector displacement. A force sensor mounted on
the wrist of the robot manipulator measures the actual force applied to
the fabric, and the formulated force error is used in order to adapt the
controllers' parameters. The performance of the controller is
investigated experimentally and the results show the effectiveness of
the FMRL approach and its wide range of applications.
The robotic handling of non-rigid objects, such as fabrics, is a very complicated problem since it is very difficult to model and predict the behavior of the fabric. The non-linearity, the large deformations and the very low bending resistance of the fabrics increase the complexity and difficulty of the robotic handling. In this paper, the robotized sewing is examined, where the fabric must be held taut and unwrinkled. Actually, a constant tensional force, which must be applied to the fabric throughout the feeding to the sewing machine, affects the seam’s quality to a great extent . Gershon clearly justified the need for force feedback control, in order to obtain a fabric’s constant tensional force in the sewing task.merritt sewing machine price in chennai,perambur, mylapore, madipakkam
While there is a big variety of force control methods on handling of rigid objects, the robotic research literature is not so rich concerning the handling of limp materials.
In the FIGARO system , a PI controller is used, where the gains were chosen by trial and error. These gains should be modified when a new type of fabric should be handled. Gershon strongly suggested that the conventional control methods are inadequate to handle the fabric tensional force. An adaptive control approach was adopted by R. Patton et.al for controlling the tensional forces applied to a fabric, where the fabric’s stiffness was the unknown variable. They mentioned that non-adaptive control schemes are unsuitable for fabric handling due to high variations of fabrics’ stiffness. Koustoumpardis et al introduced an intelligent force control scheme based on a feedforward neural network (FNN) controller, using a force sensor mounted on the robots wrist.
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