Optimisation of propylene conversion response by neuro-fuzzy approach. Issue 3 (25th September 2020)

• Record Type: Journal Article
• Authors: Shahgoli, Aiyoub Fazli; Zandi, Yousef; Heirati, Arian; Khorami, Masoud; Mehrabi, Peyman; Petkovic, Dalibor
• Is Part Of: International journal of hydromechatronics. Volume 3:Issue 3(2020)
• Page Start: 228
• Page End: 237
• Publication Date: 2020-09-25
• Subjects: polymerisation -- propylene conversion -- response -- neuro-fuzzy -- ANFIS; Fluid mechanics -- Periodicals; Hydraulic engineering -- Periodicals; Mechanical engineering -- Periodicals; Electrical engineering -- Periodicals; 620.106
• Languages: English
• ISSNs: 2515-0464

Abstract

Propylene polymerisation is a nonlinear process with complex phenomena during the reaction. In propylene polymerisation, first principle models are not appropriate to give an accurate behaviour of the reaction due to the difficulty of complex molecular structure. The difficulty is to determine the value distribution of several parameters. In addition, the morphological properties have also contributed to the difficulties of the model formulation. Therefore, empirical or semi-empirical model could be as an alternative to the mathematical model. To estimate the output propylene conversion response, the current study has built a procedure that simulates the output response regarding to different temperature, pressure and hydrogen concentration percentage with adaptive network-based fuzzy inference system (ANFIS) method. The outcomes have shown the effectiveness of ANFIS in the optimisation of propylene conversion response.