Adaptive neuro-fuzzy controller for non-linear chemical mixing process

A simple and robust method of controller is designed to improve the performance of the conventional PI controller. Fuzzy Optimization (FO) controller which is obtained from fuzzy gainscheduling concepts. In non-linear chemical mixing process, controlling and maintaining temperature is to be a difficult task. FO and Fuzzy Logic Controller (FLC) is an intelligent controller and it is used to improve the performance of Proportional-Integral (PI) controller. Neuro-Fuzzy Logic Controller (NFLC) is a fusion of fuzzy logic and neural network to get a better performance. NFLC is implemented both Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as Back Propagation Network (BPN) based Neuro-fuzzy logic. In ANFIS controller, both premise and consequent parameters are updated. It possess high accuracy and fast learning speed. The controllers are highly complex and the complexity is directly related to the cost of their implementation. The overall system is tested with non-linear chemical mixing process and the performance comparisons are made. The result shows that designed controllers are giving better performance.