Neural Network based decision support system for optimal incinerator control

In recent years there has been a significant increase in the use of AI based techniques in the field of industrial control. Different Intelligent techniques like Fuzzy Logic, Artificial Neural Network and other Hybrids have been successfully implemented for various control problems. Waste gases generated in refineries from different processes like the Claus process, cannot be directly released into the atmosphere as it has sulfur compounds and other harmful compounds. These waste gases are incinerated before discharging to make them harmless. The incineration process uses fuel gas for oxidizing waste gases, thus incinerator needs to be optimized to use minimum fuel gas and maximum oxidization. In this paper a neural network is modeled for optimal control of incinerator in Sulfur Recovery Block of refineries. Optimal control is achieved by means of an Artificial Neural Network based Inverse Plant model. The Neural Network model was developed by using the neural network tool box in MATLAB.