Meta Heuristic Optimization based Model Based Controller for a Experimental pH Process

Abstract

Achieving high-performance and robust pH control can be challenging due to the nonlinear and time-varying characteristics of the process. The pH process can exhibit significant static nonlinear behavior because the process gain can vary greatly over the modest range of pH values. Additionally, the titration curve may change over time due to unmeasured variations in the buffering capacity. These nonlinearities make it difficult to control the pH process using conventional techniques. In this study, the titration curve of the pH process is obtained through both simulation and experimentation, using weak acid (CH3COOH) as the process stream and strong base (NaOH) as the titrating stream. A conventional PI controller is designed based on the obtained process parameters for different zones of the pH process. However, the designed PI controller may not provide satisfactory responses when the operating point changes from one zone to another. To address this issue, an optimized intelligent model-based controller is proposed for the non-linear pH process in real time.