Cold-Flow Circulating Fluidized-Bed Identification

In a variety of industrial applications, the use of a circulating fluidized bed (CFB) provides various advantages, such as reducing environmental pollution and increasing process efficiency. The application of circulating fluidized bed technology contributes to the improvement of gas-solid contact, reduction of the cross-sectional area with the use of higher superficial velocities, the use of the solids circulation rate as an additional control variable, and superior radial mixing, Grace et al. [1]. In order to improve raw material usage and utility consumption, optimization and control of CFB is very important, and an accurate, real time model is required to describe and quantify the process. Currently there is no accepted way to construct a reliable model for such a complex CFB system using traditional methods, especially at the pilot or industrial scale. Three major obstacles in characterizing the system are: 1) chaotic nature of the system; 2) non-linearity of the system, and 3) number of immeasurable unknowns internal to the system,[2]. Advanced control theories and methods have the ability to characterize the system, and can overcome all three of these obstacles. These methods will be discussed in this report.