Neural network based pH control of a weak acid — Strong base system

pH neutralization is a difficult process to be controlled due to the nonlinear and time-varying process characteristics. Model Predictive Control appeared in industry as an effective means to deal with multivariable constrained control problems. This paper does the study of the pH neutralization process of a weak acid - strong base system using a neural network model predictive control technique. The simulation results are analyzed for step and random acid disturbances, which shows that the controller controls the pH within the required limits with less mean square error.