Advanced Control for a Fire-Tube Shell Boiler System

Abstract

The design of a fire-tube shell boiler consists of a bundle of tubes contained inside a shell. The heat transfer process from the combustion gas to the boiling water via the tube surface is extremely complicated as it involves combustion, convection, conduction, and boiling process. Severe boiling and evaporating processes take place outside the fire-tube shell boiler where the steam is generated. However, many processes such as the regeneration of absorbent for CO2 removal needs optimum steam consumption, which reflects its high costs for operation. Therefore, good control performance of steam pressure becomes important. This study is aimed at developing a control scheme to minimize the effect of over-firing on the fire-tube shell boiler which impacts on excessive fuel consumption. The Neural Network Predictive Controller (NNPC) is used in this work, using the optimization and neural toolboxes which are written in the MATLAB code and were compared with the PID controller for set-point tracking and disturbance rejection ability. The comparison reveals that NNPC gives an excellent alternative to PID controller due to the non-linearity of the fire-tube shell boiler system. Since NNPC can reduce the fuel consumption by minimizing actuator moves, the control of boiler and burners in this plant in Brunei is recommended to be upgraded to replace the existing PID controller.