Parameter Estimation of Reverse Osmosis Process Model for Desalination

Abstract

The present work pertains to modelling and identification of seawater desalination system using reverse osmosis. Initially the manipulated variable (feed pressure and recycle ratio) and the measured variables (flowrate, concentration and pH of permeate) are identified from reverse osmosis desalination system. The model of reverse osmosis was developed from the first principle approach using the mass balance equation (taking into consideration effect of concentration polarisation) from which the transfer function model was developed. The parameters of multi-input multi-output model are identified using the autoregressive exogenous linear identification technique. The states of the process model were also estimated using Kalman filter and parameters are identified by nonlinear least square (NNLS) algorithm. The plant’s data of spiral wound model are given as input to all the identification methods. The results obtained from the predicted and the linear models are in good agreement with these obtained for the same plant data.