Research ArticleFuzzy modeling and predictive control of superheater steam temperature for power plant

- TS fuzzy model for the SST system is developed through input-output data.
- Fictitious physical interpretation is given to the model through transformations.
- An SFMPC is designed on the fuzzy model for a wide range operation of the plant.
- The SFMPC can guarantee the input-state stability and input constraints of the plant.
- The effect of modeling mismatches and unknown plant variations has been overcome.

This paper develops a stable fuzzy model predictive controller (SFMPC) to solve the superheater steam temperature (SST) control problem in a power plant. First, a data-driven Takagi-Sugeno (TS) fuzzy model is developed to approximate the behavior of the SST control system using the subspace identification (SID) method. Then, an SFMPC for output regulation is designed based on the TS-fuzzy model to regulate the SST while guaranteeing the input-to-state stability under the input constraints. The effect of modeling mismatches and unknown plant behavior variations are overcome by the use of a disturbance term and steady-state target calculator (SSTC). Simulation results for a 600 MW power plant show that an offset-free tracking of SST can be achieved over a wide range of load variation.