Neuro-fuzzy hybrid control system of tank level in petroleum plant

Abstract

Shown in this paper is a practical method of control using neural network and fuzzy control techniques, where a neural network estimates the target of fuzzy control. The neural network is used to estimate the transient state of a plant which has nonlinear processes such as refrigerating and filtering. The suitable control target pattern for fuzzy control is selected according to this estimation. This method is applied to control the tank level of a solvent dewaxing plant for: 1) changing the tank outflow rate smoothly, and 2) keeping the tank level stable. The results show that this system can control the tank level effectively in both steady state and transient state.