Control Improvement Using MPC: A Case Study of pH Control for Brine Dechlorination

Abstract

This paper describes a case study carried out to quantify the benefits achieved from the application of model predictive control (MPC) to regulate the pH in a brine dechlorination process. A mechanistic model of the process was developed and used to design a PI controller with feedforward compensation. The model was also used to quantify the potential benefits of commissioning an MPC controller on the process. Following the analysis with the mechanistic model, the designed MPC scheme was applied to the actual process. Through real-time results, it is shown that the deployment of this controller led to substantial improvements in disturbance rejection capabilities when compared to the existing PI controller with lead- lag feedforward compensator. The improved disturbance rejection led to a reduction in pH variation which resulted in reduced operational costs, more reliable production, and improvement in the efficiency of the dechlorination process.

Keywords

• Brine dechlorination
• control system synthesis
• mechanistic model
• model-based control
• pH control
• predictive control