Tsukamoto Fuzzy Logic Controller for Motion Control Applications: Assessment of Energy Performance

Abstract

This work presents a control strategy designed to reduce the energy consumption of direct current motors by implementing smooth motion trajectories in a point-to-point control system, utilizing a fuzzy logic controller based on the Tsukamoto inference method. The proposed controller’s energy performance was experimentally compared to that of a conventional PID controller, considering three motion profiles: parabolic, trapezoidal, and S-curve. The results demonstrate that the combination of the fuzzy controller with smooth trajectories effectively reduces energy consumption without compromising motion accuracy. Under no-load conditions, average energy savings of 11.77% for the parabolic profile, 9.27% for the trapezoidal profile, and 3.45% for the S-curve profile were achieved. This improvement remained consistent even when a load was introduced to the system. To validate these findings, the coefficient of variation was calculated, revealing lower dispersion in the fuzzy controller’s results, indicating greater consistency in energy efficiency. Furthermore, Welch’s t-tests were conducted for each profile and load condition, with all p-values falling below the 0.05 significance threshold, confirming the statistical relevance of the observed differences.