Abstract
This paper describes the simulation of movement control of a one-degree-of-freedom articulated robot arm SCARAactuated by a pair of McKibben pneumatic artificial muscles. The pneumatic artificial muscle is the actuator andemulates the behavior of biological muscles; due to its nonlinear behavior, there is also a need to develop controlsystems for robot arms using this type of actuator. Research begins with the transfer function that represents, inmathematical language, the movement of the robot arm’s joints; this allows using a PID controller on the transferfunction and generating data to train the Multilayer Perceptron Artificial Neural Network (RNAPM). So far, the PIDcontrol system has been able to control the movement of robot arms but, based on experimental tests, the RNAPMhas 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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