Model Predictive Control of the Reverse Osmosis Plant at AICA Laboratories

Abstract

Process control is an essential part of the desalination industry that requires to be controlled at theoptimum operating conditions to guarantee an increase in the life time of the plant and reduction of theunit product cost. Desalination is a highly complex process, so the majority of dynamic models are ofthe form of Multi-Inputs-Multi-Outputs (MIMO) systems. Controlling a MIMO system is a complexoperation because of the interconnections between the inputs and the influence of each one of them onthe system outputs. In this paper, we present the MIMO dynamic model that was developed for a twostageReverse Osmosis (RO) desalination system at AICA Laboratories. The purpose of this researchwas to apply a new control strategy to the system based on a Model Predictive Control (MPC) algorithm.The control system proposed was simulated through computer by using Simulink/Matlab software.The simulation results show the efficiency of the proposed controller based on MPC strategy and canbe useful to increase knowledge in control processes in reverse osmosis desalination systems.