| dc.description.abstract | BLDC motor is the most widely used in the industrial world, especially in electric vehicles. With this increasing demand, a variety of research topics emerged in BLDC motors. One popular research is on BLDC motor speed control
topics to maintain speed for its application, such as intelligent cruise technology in electric cars and conveyors for
line assembly. However, from several existing studies, the BLDC Motor controller still uses a single controller model.
The controller's output is purely from the controller without any improvement in characteristics and has a problem
with the oscillating speed setpoint (error problem). In this study, the researcher proposed a combining control with
the concept of summation output to handle this problem. With this concept, the control techniques used can improve
each other so that better control can be produced following the control system assessment parameters. The authors
used a Fuzzy Logic Controller, Artificial Neural Network (ANN), and PID, which were combined and obtained seven
control systems. The results show that the control system can improve several parameters using the summation
concept from the seven controllers model. It has a positive overall correlation when viewed in terms of the difference
between the Error and the setpoint or MAE (Mean Absolute Error) as parameter assessment. | en_US |
