My Publications

 

Book: Transactions on Engineering Technologies

Springer 2014, Book ISBN: 978-94-017-9114

This paper examines the procedure for a nonlinear modeling and fuzzy controller design of a Fluidized Catalytic Cracking Unit, also known as FCCU. The case study is an FCCU plant in Abadan Refinery, Iran. FCCU is one of the most important sections in the Petrochemical industry. In 2006 alone, FCCUs refined one-third of the Crude Oil worldwide. FCCUs convert heavy distillates, such as Gasoil (feed) and Crude Oil, to Gasoline, Olefinic gases and other more usable products. Factors including but not limited to FCCU’s high efficiency, and daily price fluctuations in Gas, Oil and Petrochemical products, make the optimization of such units the center of focus for both engineers and investors. Unlike the conventional controllers, Fuzzy Logic is the perfect choice for stochastic, dynamic and nonlinear processes where the mathematical model of the plant cannot be produced, or if realizable, a great deal of approximation is involved. The heuristic approach in Fuzzy Logic controllers is the closest form to the human language, and this virtue will make it a perfect candidate for a wide range of industrial applications. The investigations in this paper are simulated and proven by MATLAB Fuzzy Logic Toolbox R2013a. In this paper, the applicability and promising features of Fuzzy Logic controllers for such a complex and demanding plant will be investigated.


Fuzzy Logic Controller for Fluidized Catalytic Cracking Unit - FCCU

This paper examines the procedure for nonlinear modeling and Fuzzy controller design of a Fluidized Catalytic Cracking Unit, also known as FCCU, of Abadan Refinery in Iran. FCCU is one of the most important elements in Petrochemical industry. In 2006 alone, FCCUs refined one-third of the crude Oil worldwide. FCCUs convert the heavy distillates like Gasoil (feed) and Crude Oil to Gasoline, Olefinic gases and other more usable products. Since FCCUs yield large amount of products very efficiently, along with the Petrochemical products’ daily price fluctuations, the optimization of such units has always been the focus of attention for engineers as well as investors. Unlike the conventional controllers, Fuzzy Logic is the perfect choice for uncertain, dynamic and nonlinear processes where the mathematical model of the plant cannot be produced, or if realizable, a great deal of approximation is involved. The heuristic approach of Fuzzy Logic controllers is the closest form to human language, and this virtue will make them a perfect candidate for a wide range of industrial applications. The investigations in this paper are simulated and proven by MATLAB Fuzzy Logic Toolbox R2012b. Through this paper, the applicability and promising results of Fuzzy Logic controllers for such a complex and demanding plant will be investigated.


The Hamming Code Performance Analysis using RBF Neural Network

In this paper the Hamming decoding model development, and BER curve performance, including Error histogram, target Mean Square Error, Training state, Regression curve and the impact of employing a different number of Neurons in RBF Neural network will be investigated. The Hamming (15,11) will be used to develop the results, and diagrams throughout this article. The results, and simulations in this paper are generated via Matlab Neural Network Toolbox 2013.