Robust nonlinear model predictive control for a PWR nuclear power plant

One of the important operations in nuclear power plants is power control during load following in which many robust constraints on both input and measured variables must be satisfied. This paper proposes a robust nonlinear model predictive control for the load-following operation problem by considering some robust constraints on both input and output variables. The controller imposes restricted state constraints on the predicted trajectory during optimization which guarantees robust satisfaction of state constraints without restoring to a min-max optimization problem. Simulation results show that the proposed controller for the load-following operation is quite effective while the constraints are robustly kept satisfied.

► In this work, a robust nonlinear model predictive control algorithm is developed.
► This algorithm is applied to control a PWR Nuclear Power Plant.
► The state constraints are imposed on the predicted trajectory during optimization.
► Robust satisfaction of state constraints is guaranteed.
► This guarantee is result without restoring to a min–max optimization problem.