Design of a closed-loop statistical data controller for a servomechanism using a self-tuning technique - Ojeda-Misses, M.A.; Martines-Arano, H.; Sampedro-Mendoza, A.; Franco-Árcega, A.; López-Morales, V. (RIIIT Revista Internacional de Investigación e Innovación Tecnológica, 2025)
This work proposes and applies a technique based on statistical data for the design of a Proportional and a Proportional Integral controller for speed, both capable of self-tuning their gains. The self-tuning technique is based on the statistical analysis of the system output, performing a sampling to calculate the mean and standard deviation, and using the value of z according to the central limit theorem. From this analysis, the probability level is estimated, which allows a mapping from the probabilistic space to the controller gain space, using a sigmoid function to adjust the gains online. The controller performance is evaluated and compared in two first-order systems, one stable and the other unstable, as well as in a real-time speed control servomechanism. The self-tuned statistical proportional-integral controller is compared with equivalent controllers tuned using Matlab’s pidtune, highlighting the effectiveness of the proposed technique in the automatic adaptation of the controller.