Control System Design based Neuro fuzzy Algorithm for Modified Robotic System PUMA560
In robotics, a design of computational system is an important issue which is enabled to represent the functions of robotics and learning the robotic brain to control motions. AI technologies and such neural network enables to to diagnose the error resulting from the movement of the robot by training it to compare the values given to the network through tables in the form of matrix and the real values of the movement of the robot to give the network output to the correct movement of the robot. This paper provides a design of a neural network system for robotics to control the robot movement through a programming and control interface. The evaluation results show the proposed design describing the transit response analysis of the joint actuator (robot motors) to ensure the stability and synchronous will be done.
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