Intelligent tuning of the 2-DOF PID controller on the DCS for steam temperature control of thermal power plant

In the thermal power plant, there are six manipulated variables; main steam flow, feedwater flow, air flow, spray flow, and gas recirculation flow. Also, there are five controlled variables such as generator output, main steam pressure, main steam temperature, exhaust gas O density, and reheater steam temperature. Therefore, the thermal power plant control system is a multi-input and output system. In the control system, the main steam temperature typically is regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. However, it is difficult to maintain strict control of the steam temperature in order to avoid thermal stress, because of variation of the heating value according to the fuel source, the time delay of changes in main steam temperature versus changes in fuel flow rate, difficulty of control on the main steam temperature control and the reheater steam temperature control system owing to the dynamic response characteristics of changes in steam temperature and the reheater steam temperature, fluctuation of inner fluid water and steam flow rates widely during load-following operation. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the characteristic comparison of the PID controller, the modified 2-DOF PID Controller on the DCS, in order to design an optimal controller which can be operated on the thermal generating plant in Seoul, Korea. The modified 2-DOF PID Controller is designed with a 2-degrees parameter, to enable them to fit into the thermal plant during disturbances vs. many kinds noises and load-following operation. In order to attain an optimal control method, transfer function and operating data from start-up, running, and stop procedures of the thermal plant have been acquired. Through this research, the stable range of a 2-DOF parameter for only this system could be found for the start-up procedure and this parameter could be used for the tuning problem. Also, this paper tried whether intelligent tuning method based on the immune network algorithms can be used effectively in a tuning for these controllers.