On the application of predictive functional control in steam temperature systems of thermal power plant

Predictive functional control (PFC) is applied to steam temperature systems. Firstly, PFC algorithm for first-order plus dead-time system is provided, another novel PFC algorithm based on finite impulse response (FIR) model is also presented. Combining the novel algorithm, T-S fuzzy modeling and adaptive control technique, fuzzy adaptive predictive functional control (FAPFC) strategy is presented. Predictive functional control-proportional (PFC-P) cascade control strategy is designed in superheated steam temperature systems. In order to get over the influence of load variety, FAPFC strategy is applied to superheated steam temperature systems. The step response results show that the superheated steam temperature system with PFC-P cascade control strategy has favorable dynamic performance, and is distinctly better than the system with traditional proportional-integral-differential (PID) cascade control strategy. And computer simulation results of load adaptability experiments show that the system has good load adaptability. The variety of main steam temperature is under ±5°C and manipulated variable changes smoothly under large-scale variety of load. In addition, considering a large class of multi-input and multi-output (MIMO) system that can be equivalently described as first-order plus dead-time plant in each process channel, multi-variable PFC algorithm is presented based on feed-forward compensation decoupling technique. The algorithm is applied to a multi-variable steam temperature process with steam-steam heat exchanger in a 200 MW unit. Computer simulation results show that the control strategy is effective, the almost dynamic decoupling and completely static decoupling function are obtained, and the closed loop system has zero static error. Many experiments under mismatches between the controlled plant and the prediction model demonstrate the strong robustness and disturbance rejection of the strategy.