Minimum-Variance Model Predictive Control for Dual Fluidized Bed Circulation Control

Abstract

Dual fluidized bed steam gasification enables the production of gaseous energy carriers from woody biomass or biogenic residues. The circulation of bed material in dual fluidized bed gasifiers strongly affects the process behavior. Therefore, precise control of the bed material circulation is desired. This paper presents a control algorithm addressing two aspects of the given problem setting: On the one hand, redundant control actuators are available. Typically, there are several air streams to the reactors influencing the bed material circulation. On the other hand, only black box models with uncertainties in their model parameters are available for model-based control design. The presented control algorithm uses a model predictive controller considering known uncertainties in the model parameters and drives the process in a region with the lowest model uncertainties. This results in an improvement of the closed-loop performance when the actual plant deviates from the internal model used for the model predictive control predictions. Simulations show 66 % less offset from the design trajectory with the presented algorithm when compared to a standard model predictive controller.