A new practical feed-forward cascade analyze for close loop identification of combustion control loop system through RANFIS and NARX

Abstract Boiler-turbine is a multi-variable and complex system in steam power plants including combustion control loop, temperature control loop and drum water level control loop, where each of them are separate control loops. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complex task, because of nonlinear time variant dynamic characteristics of the boiler. In the present article, a realistic and efficient model of the combustion control loop of the 320 MW steam power plant of Islam Abad, Isfahan is identified separately from other control loops of the boiler, unlike similar articles. Another critical point about this article is being superior to the others, due to identifying the combustion control loop system by feed-forward cascade analysis. Due to the sensitivity and complexity of the system, with respect to its nonlinear and closed loop characteristics, the combustion control loop system is considered as a feed-forward cascade and the identification of the system is carried out during the load changes and conducted through intelligent procedures like recurrent adaptive neuro-fuzzy inference system (RANFIS) and nonlinear autoregressive model with exogenous input (NARX). The obtained results through actual data collected from the plant are presented and the accuracy of the procedures is determined.