DYNA, ISSN 0120-5609, 0012-7353, Volume 89, number 220, 2022, pp. 178-186, Issue published: Feb 1, 2022

DOI: https://doi.org/10.15446/dyna.v89n220.96502

Regardless of the advances in intelligent control the analysis and use of the human capacity to control are far from exhausted. For instance, industrial applications could be too fast or too slow for a human to control. The proposed solution in this paper starts by scaling the model of the system in time, so that it results comfortable to control. The control actions of the human are learned by a Neural Network, which is blind to the changes in the time scale, thus the Neural Network controls the scaled model and the real plant as well. The Time Scaling Controller is evaluated by controlling the angular position of a motor and the result is contrasted with a fuzzy controller and a piecewise linear controller. Time Scaling Control resulted better than the other two controllers because it has the lowest effort and the highest effectiveness among the three controllers.