Implementation of Fuzzy Logic Based Speed Control of Brushless Direct Current Motors via Industrial PC

  • Süleyman ÇEVEN
  • Raif BAYIR
Keywords: fuzzy logic, speed control, industrial pc

Abstract

The brushless direct current motors are often preferred in the industry due to their high development torques, efficiencies, speed and position controls. Especially, they are used with robotic, numeric-controlled machines, electrical vehicles, etc. One of the biggest difficulties of these motors is the closed loop operation of these motors with driver circuits and a controller. In this study, the speed control of the brushless direct current motors was made with PLC-based industrial computer by using the methods of PID and Fuzzy Logic. PLC based industrial computer of Beckhoff firm CX9020 was preferred as a controller. In this industrial computer, the software of the controller was developed by using Structured Text programming language of Twincat 2.11 program. In experimental studies, the speed control of the brushless direct current motors is made with PID and fuzzy logic controller, according to the requested reference. The performances of the controllers were tested by using step, ramp and ladder functions. While PID controller gave better results in reference speed areas whose parameters were determined, fuzzy logic controller gave better results in variable references. Although PID is given as a ready block in PLC and PLC based controllers, fuzzy logic is under development in many of them. In this study, classical PLCs and PLC based industrial PCs, which did not have any fuzzy logic controller module, were transformed into intelligent controllers with Structured Text programming language. As a result of this, classical PLCs and PLC based industrial PCs can be used in intelligent control, which is very important for industry 4.0.

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References

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Published
2016-12-26
How to Cite
[1]
S. ÇEVEN and R. BAYIR, “Implementation of Fuzzy Logic Based Speed Control of Brushless Direct Current Motors via Industrial PC”, IJISAE, pp. 146-152, Dec. 2016.
Section
Research Article