DC Motor Speed Control Based on Fuzzy Adaptive with Fuzzy Model Reference Learning Control (FMRLC) Algorithm

Fuzzy Model Reference Learning Control (FMRLC) is a control technique developed by extending several self-organizing linguistic control concepts and utilizing ideas from the conventional Model Reference Adaptive Control (MRAC) method. FMRLC in this study is used to control the speed of a DC motor. FMRLC testing is performed on the step response, set point with a constant value, tracking setpoint, and torque load. The test results show the adaptive fuzzy control system with the FMRLC algorithm to control a DC motor’s rotation speed can be well designed, proven by simulating the FMRLC control system using MATLAB. The performance of the FMRLC control system that has a design to control the rotation speed of a DC motor at a set point of 3000 rpm without load includes: delay time = 0.0681 seconds, rise time = 0.2279 seconds, setting time = 0.3863 seconds. For DC motors at 3000 rpm, setpoint load ½ torque raises a steady-state error of 0.0207%, with a max torque load resulting in a steady-state error of 0.0413% and when given a load of 2x maximum torque produces a steady-state error of 0.0818%, with each of the following sequential recovery times 0.6457 seconds 0.7939 seconds and 0.7532 seconds.