Control Improvement of Low-Cost Cast Aluminium Robotic Arm Using Arduino Based Computed Torque Control

Authors

  • Petrus Sutyasadi Sanata Dharma University

DOI:

https://doi.org/10.26555/jiteki.v8i4.24646

Keywords:

Robot arm, Low-cost, Arduino, Computed Torque Control, Feedback Linearization

Abstract

Gravity causes non-linearity in position control of an articulated industrial robotic arm. Especially for a joint position control of a robot’s shoulder and elbow that works parallel with the gravity direction. To overcome the problem, Computed Torque Control algorithm was implemented. This algorithm linearized the feedback, so a regular linear Proportional Derivative controller can be implemented. The contribution of this research is to find an effective controller to control a heavy weight low-cost robotic arm link/body using low-cost controller such as Arduino. A Computed Torque Control was implemented to control the shoulder joint of an articulated robotic arm. This joint is the most affected joint by the gravity. It works along the vertical plane, and loaded by the rest of the arm and the robot’s load. The proposed controller was compared to a Proportional Integral Derivative (PID) Controller and a Cascade PID Controller. The experiment showed that the Computed Torque Controller can control the position of the arm properly both in the direction along or against the gravity. A linear PID controller could not bring the arm to the set point when it moves against the gravity, but it works well when the arm moves in the opposite direction. A Cascade PID controller has an overshot when the arm moves along the gravity. But it works properly when it moves up against the gravity. A Computed Torque Control works well in both directions even in the presence of gravity force because it includes the gravity on its algorithm.

Downloads

Published

2022-12-21

How to Cite

[1]
P. Sutyasadi, “Control Improvement of Low-Cost Cast Aluminium Robotic Arm Using Arduino Based Computed Torque Control”, J. Ilm. Tek. Elektro Komput. Dan Inform, vol. 8, no. 4, pp. 650–659, Dec. 2022.

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