**7. Conclusions**

This paper presents a novel economic steady-state optimal control method for control of energy systems in buildings. The control method used economic objective functions that were based on real data from systems found in the Utilities Business Office at Texas A&M University to minimize the economic cost associated with operating the building. Specifically, the cost of utilities (electricity and chilled water) were optimized alongside the cost of loss productivity due to occupant discomfort. In these optimizations, the effect of practical realities that are under represented in the literature were taken into account, including humidity and its effect on comfort, the switching behavior of systems due to mechanical limits, and the effect of current operating conditions on the optimization. Co-simulations of the steady-state optimization controller applied to the Utilities Business Office building were performed with EnergyPlus and MATLAB. The simulation results show improved comfort performance and economic savings with the use of the steady-state optimization controller over the current control method implemented. While the proposed algorithm was deliberately applied to one AHU, the basic structure allows for the optimization of larger building systems that could include several chillers, AHUs, dozens of VAVs, and hundreds of zones.

**Author Contributions:** Conceptualization, C.J.B. and B.P.R.; methodology, C.J.B., R.C., and B.P.R.; software, C.J.B. and R.C.; validation, C.J.B. and B.P.R.; formal analysis, C.J.B.; investigation, C.J.B.; data curation, C.J.B.; writing—original draft preparation, C.J.B.; writing—review and editing, C.J.B., R.C., and B.P.R.; visualization, C.J.B.; supervision, B.P.R.; project administration, B.P.R.; and funding acquisition, B.P.R. All authors have read and agreed to the published version of the manuscript.

**Funding:** This material was based on work supported by the National Science Foundation under Grant No. NSF CMMI-1563361. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

**Acknowledgments:** The authors would like to recognize Texas A&M University's Utilities Energy Management Office, specifically Chris Dieckert, for their contribution of building data and access.

**Conflicts of Interest:** The authors declare no conflict of interest.
