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This paper describes the simulation of movement control of a one-degree-of-freedom articulated robot arm SCARA actuated by a pair of McKibben pneumatic artificial muscles. The pneumatic artificial muscle is the actuator and emulates the behavior of biological muscles; due to its nonlinear behavior, there is also a need to develop control systems for robot arms using this type of actuator. Research begins with the transfer function that represents, in mathematical language, the movement of the robot arm's joints; this allows using a PID controller on the transfer function and generating data to train the Multilayer Perceptron Artificial Neural Network (RNAPM). So far, the PID control system has been able to control the movement of robot arms but, based on experimental tests, the RNAPM has proved to outperform the PID control's response time by up to 2.95 seconds, minimizing the angular error by 1.3° and avoiding the oscillation problem due to its continuous, constant behavior.
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