Disturbance Rejection Model Predictive Control of Ultra-Supercritical Once-Through Boiler-Turbine Unit

The regulation of boiler-turbine unit in ultra-supercritical power plant is vulnerable to various unknown disturbances. To overcome this issue, this paper proposes the extended state observer based disturbance rejection model predictive control for the boiler-turbine unit. State space model is firstly established on the basis of subspace identification. To enhance the disturbance rejection property of the controller, the technique of extended state observer is employed to estimate the unknown disturbances. The disturbance estimation based model predictive controller is then devised. The observer gain is designed using a less conservative linear matrix inequality, which will accelerate the convergence speed of estimation error. The effectiveness of the proposed controller is illustrated by simulations.