APPLICATION OF THE STRUCTURED CONTROL LANGUAGE IN BUILDING THE NEURAL NETWORK BASED PID INTEGRATED IN THE PROGRAMMABLE LOGIC CONTROLLER
DOI:
https://doi.org/10.11113/aej.v16.23771Keywords:
Structured control language, Radial basis function, PID controller, Programmable logic controller, Neural networkAbstract
Programmable Logic Controllers (PLC) have been developed and deployed mainly in industry because of their reliability and stability in a harsh environment. The PLCs have been integrated with stronger processors, input/output modules, and modern communication protocol. Therefore, they are not only ideal for working in industrial zones but also in testing automotive algorithms. This paper aims to apply the structured control language (SCL) to directly implement the radial basis function neural network (RBFNN) into a Siemens PLC, two RBFNN-based adaptive proportional–integral–derivative (PID) controllers were implemented to control the working temperature of a metal–oxide–semiconductor field-effect (MOSFET) transistor named IRFZ44N via changing the gate voltage. The experimental results show that, the RBFNN is working correctly in PLC and could be adapted by the PID controller to improve the temperature response in comparing with the PID controller integrated in the PLC (model: S7-1200, CPU 1215C DC/DC/DC) 48.1% and 30% in terms of the overshoot and steady state error, respectively. Moreover, the control rules of the proposed structure have eliminated the output chattering which reduced the negative effect on the actuators. These results also proved the ability of deploying some modern control algorithms on the PLCs and applying the PLC in testing the control theory.
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