CFD for model-based controller development

This paper outlines a novel approach to model and control the internal dynamics of energy and mass transfer in an imperfectly mixed fluid. The essential element in the approach lies in the extension of a complex CFD simulation model with a simplified, low-order representation of the process using a mathematical identification technique. The reduced-order model that characterises the dominant modes of dynamic behaviour forms an excellent basis for on-line model-based control purposes. Most control algorithms are designed based on experimental time-series data, unlike the others this paper discusses a methodology to use numerical predictions for controller development. This has important practical advantage for control applications especially when experimentation is difficult or in some extreme cases impossible. Furthermore, the inspiration of using numerical predictions instead of experimental time-series data allows designing virtual climate control systems, which launches new possibilities to large number of applications. In this paper, the general methodology will be elaborated using multiple-input–multiple-output (MIMO) ventilation system, and later on the approach will be applied for a single-input–single-output (SISO) ventilation system.