Tuning of a temperature controller through a programmable automatism

The implementation of PID controllers in industry has as main difficulty the programming of automatisms in charge of processes, which usually is translated into on-off controllers without any kind of tuning. The goal of this research was to stablish the behaviour of some techniques of constant tuning, in a commercial programable logic controller, evaluating them into a temperature system. The system is composed of a container with water, a PID controller in the PLC s7-300, making use of the temperature control module Siemens FM 355-2C, a resistance heater AC as actuator (controlled by DC voltage), and thermocouple type as a temperature sensor. The mathematical model of the system, as well as the constants of the PID controller, were obtained making use of the Matlab PID Tuner computational tool. The identification techniques studied were: MLP neural network, the non-linear auto-regressive network with exogenous inputs (NARX) and the neuro-diffuse network (ANFIS). The results show that the previous techniques are adequate to tune a PID contoller, being useful in industrial prosecess.

• Tipo de recurso: http://purl.org/coar/resource_type/c_6717
• Fecha de publicación: 2018
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/10290
• Acceso en línea: https://revistas.uptc.edu.co/index.php/investigacion_duitama/article/view/8513; https://repositorio.uptc.edu.co/handle/001/10290
• Palabra clave: temperature control; PLC; identification techniques; neural networks; PID controller.; control de temperatura; PLC; técnicas de identificación; redes neuronales; controlador PID.
• License: Derechos de autor 2018 REVISTA DE INVESTIGACIÓN, DESARROLLO E INNOVACIÓN