Adaptive Fuzzy Control of a pH Process

The process of pH process control is a challenging problem due to the strong nonlinearity and extreme sensitivity to disturbances of the process. This paper presents an application of one-step-ahead adaptive fuzzy control scheme for a strong acid-strong base neutralization process. The controller is designed based on a Mamdani type fuzzy system constructed to model the dynamics of the process. The fuzzy system model can take advantage of both a priori linguistic human knowledge through parameter initialization, and process measurements through online parameter adjustment using the least square algorithm with deadzone. In both setpoint tracking and disturbance rejection tasks, simulation experiments show satisfactory performances of the resulted pH control scheme as well as performance improvements owing to the linguistic information.

I. Introduction

pH process control is common and important in chemical industries such as biological, wastewater treatment, electrochemistry and coagulation/precipitation systems. The purpose of pH control is to adjust the pH to a specified value for certain requirements, for example, to minimize the environmental impact in wastewater treatment systems or to maximize reaction speed or product yields in chemical reactions. The challenge of pH control lies in that the process gain can change by several orders of magnitude over the pH range, due to the high nonlinearity resulted from the logarithmic relation between the pH value and the concentration of the hydrogen ions. Furthermore, especially around the neutralization point, the process is very sensitive to perturbations, such as the changes of flow rates, concentrations or buffering capacities of the input streams.