Adaptive fuzzy control of a pH process

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. © 2006 IEEE