Nonlinear model predictive control (NMPC) scheme is an effective method of multi-objective optimization control in complex industrial systems. In this paper

a NMPC scheme for the wet limestone flue gas desulphurization (WFGD) system is proposed which provides a more flexible framework of optimal control and decision-making compared with PID scheme. At first

a mathematical model of the FGD process is deduced which is suitable for NMPC structure. To equipoise the model's accuracy and conciseness

the wet limestone FGD system is separated into several modules. Based on the conservation laws

a model with reasonable simplification is developed to describe dynamics of different modules for the purpose of controller design. Then

by addressing economic objectives directly into the NMPC scheme

the NMPC controller can minimize economic cost and track the set-point simultaneously. The accuracy of model is validated by the field data of a 1000 MW thermal power plant in Henan Province

China. The simulation results show that the NMPC strategy improves the economic performance and ensures the emission requirement at the same time. In the meantime

the control schem

e satisfies the multiobjective control requirements under complex operation conditions (

e.g

.

boiler load fluctuation and set point variation). The mathematical model and NMPC structure provides the basic work for the future development of advanced optimized control algorithms in the wet limestone FGD systems.