Nasser Saghatoleslami
Department of Chemical Engineering, University of Ferdowsi, P.O. Box 9177948944 Mashhad, I. R. IRAN
[ 1 ] - Comparative Study of Artificial Neural Networks (ANN) and Statistical Methods for Predicting the Performance of Ultrafiltration Process in the Milk Industry
Milk ultrafiltration is a membrane process, which is highly complex innature. The cost effectiveness of the process depends heavily on the flux permeate and the total hydraulic resistance of the membrane. In this work, a comparative study for the prediction of the performance of milk ultrafiltration with ANN and statistical method has been carried out. The result reveals that both methods c...
[ 2 ] - Identification and Control of MIMO Systems with State Time Delay (Short Communication)
Time-delay identification is one of the most important parameters in designing controllers. In the cases where the number of inputs and outputs in a system are more than one, this identification is of great concern. In this paper, a novel autocorrelation-based scheme for the state variable time-delay identification for multi-input multi-output (MIMO) system has been presented. This method is ba...
[ 3 ] - Controlling Nonlinear Processes, using Laguerre Functions Based Adaptive Model Predictive Control (AMPC) Algorithm
Laguerre function has many advantages such as good approximation capability for different systems, low computational complexity and the facility of on-line parameter identification. Therefore, it is widely adopted for complex industrial process control. In this work, Laguerre function based adaptive model predictive control algorithm (AMPC) was implemented to control continuous stirred tank rea...
[ 4 ] - A Neuro-Fuzzy Model for a Dynamic Prediction of Milk Ultrafiltration Flux and Resistance
A neuro-fuzzy modeling tool (ANFIS) has been used to dynamically model cross flow ultrafiltration of milk. It aims to predict permeate flux and total hydraulic resistance as a function of transmembrane pressure, pH, temperature, fat, molecular weight cut off, and processing time. Dynamic modeling of ultrafiltration performance of colloidal systems (such as milk) is very important for design...
[ 5 ] - Modeling of Texture and Color Froth Characteristics for Evaluation of Flotation Performance in Sarcheshmeh Copper Pilot Plant, Using Image Analysis and Neural Networks
Texture and color appearance of froth is a discreet qualitative tool for evaluating the performance of flotation process. The structure of a froth developed on the flotation cell has a significant effect on the grade and recovery of copper concentrate. In this work, image analysis and neural networks have been implemented to model and control the performance of such a system. The result reveals...
Co-Authors