Design and Implementation of Real Time Neurofuzzy Based pH Controller

The quality of an intelligent control system is the ability to control the process with a certain degree of autonomy. These requirements, as an autonomous process controller are ever increasing. Considering the fact that existing algorithm based controllers such as the adaptive PID have their own limitations/are inadequate, the controllers are designed to emulate human mental faculties such as adaptation, learning, and planning under uncertainties and also coping up with large amounts of data by reducing the complexity of their representation. The family of intelligent controllers includes those based on neural nets, fuzzy logic, classic artificial intelligence and the genetic algorithms. This paper describes design and development of real time neurofuzzy based pH controller, which can be used in water treatment processes, laboratory studies and other industrial applications.