Control of ultra-supercritical once-through boiler-turbine unit using MPC and ESO approaches

Abstract

In order to meet the wide-range load tracking requirement and overcome unknown disturbance issues of ultra-supercritical (USC) boiler-turbine unit, an extended state observer based fuzzy model predictive controller is proposed using the techniques of fuzzy scheduling, model predictive control and extended state observer. Local state-space models are established on the basis of nonlinearity analysis. Then a fuzzy stable model predictive controller is devised on the fuzzy model using output cost function for the purpose of wide-range load tracking. An improved linear extended state observer, which can estimate plant behavior variations and unknown disturbances regardless of the direct feedthrough characteristic of the boiler-turbine unit, is synthesized with the predictive controller to enhance its disturbance rejection capability. The simulation results on a 1000MW USC boiler-turbine unit model verify the merits of the proposed strategy in achieving the satisfactory wide-range load tracking and disturbance rejection performance.