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Abstract
In this study, the auto-tuning proportional-integral controller is used to control the speed of a switched reluctance motor. The control algorithm is executed by the programmable logic controller. The proportional integral gains are determined via fuzzy logic. Fuzzy logic is executed on a separate computer via MATLAB/Simulink software. The data exchange between the programmable logic controller and MATLAB/Simulink is done with object linking embedding/component for the process. The fuzzy proportional integral control algorithm is compared with the conventional proportional integral controller. We reduced the load on the programmable logic controller via executing fuzzy logic in a separate computer and at the same time eliminated the disadvantages of the conventional proportional-integral controller. With the proposed method, the engine reached the reference speed value in a short time and the overshoots were eliminated in variable conditions such as different load and different speed conditions.
Highlights
The speed control of the motor is important to achieve maximum torque and efficiency in industrial applications
Programmable logic controller (PLC) is generally preferred as a controller, and the programmable logic controller (PLC) are often considered as the main workhorses of the systems.[1]
Switched reluctance motors (SRMs) is preferred in industrial applications due to its simple structure, low cost, high torque production, stability, and work ability at very high speeds and brushless structure.[2]
Summary
The speed control of the motor is important to achieve maximum torque and efficiency in industrial applications. Panda et al.[11] highlight that the fuzzy PI controller in the speed control of the SRM is more stable than the conventional PI controller at different reference speeds. Vijayan et al.[14] claim that the SRM responds better to the speed control than the fuzzy PI controller following the reference, producing less steady-state error and insensitive to disturbance load than conventional control methods. There are various remote control applications using OPC and PLC communication.[17,18,19,20,21] Lieping et al.[22] have exchanged data between PLC and MATLAB using OPC and have shown that it is possible to obtain advanced solutions in complex industrial automation systems. The innovation in this work is the use of communication technology in SRM motor speed control. The advantage of this study and future scope of the paper are discussed
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