Title : Controlling the production process of unplasticized polyvinyl chloride profile using adaptive neural fuzzy inference system
Abstract:
Decisions made regarding the production process in manufacturing and industrial locations have always been complex and challenging. Extrusion is one of the main methods of processing polymer materials and plays a role in the final production of various types of polymer products, including UPVC (Unplasticized Polyvinyl Chloride) profiles. Controlling the production process of UPVC profiles to achieve the desired output both qualitatively and quantitatively requires human activities with precision and focus. Since the mentioned production process is a non-linear process and many effective factors are involved in its control, the importance of developed and intelligent controllers becomes more apparent. One of these controllers is the fuzzy neural controllers, which cause better control of the device, increase work efficiency and production of quality profiles. Fuzzy neural controllers are used to solve problems of systems that do not have precise mathematical relationships between inputs and outputs. In this paper, an intelligent control system based on ANFIS (Adaptive Fuzzy Neural Inference System) has been used to control the production process of UPVC profiles. The simulation results in MATLAB show that an optimal model can be achieved with ANFIS and data taken from the real system and the hybrid training method to achieve the desired output with less error.
