ABSTRACT
This chapter offers a treatment of the role of building automation and control systems in the context of building performance modeling. In particular, we motivate the use of models for the advanced control of building energy systems by offering application examples employing dynamic models for online and offline predictive optimal control tasks. The chapter introduces model categories that reflect the degree to which physical first principles have been employed and compares procedures for calibrating such models using least squares and probabilistic approaches, both extensively illustrated by an example. Moreover, the chapter describes several current building-related examples of offline and online model predictive control as well as the application of rule extraction to the control of commercial buildings employing mixed mode ventilation.
