Advanced control strategies for heating, ventilation, air-conditioning, and refrigeration systems—An overview: Part I: Hard control

Abstract

A chronological overview of the advanced control strategies for heating, ventilation, air-conditioning, and refrigeration (HVAC&R) is presented in this article. The overview focuses on hard-computing or control techniques, such as proportional-integral-derivative, optimal, nonlinear, adaptive, and robust; soft-computing or control techniques, such as neural networks, fuzzy logic, genetic algorithms; and on the fusion or hybrid of hard- and soft-control techniques. Thus, it is to be noted that the terminology “hard” and “soft” computing/control has nothing to do with the “hardware” and “software” that is being generally used. Part I of a two-part series focuses on hard-control strategies, and Part II focuses on soft- and fusion-control in addition to some future directions in HVAC&R research. This overview is not intended to be an exhaustive survey on this topic, and any omission of other works is purely unintentional.

Acknowledgment

The funding provided for this research activity, performed under subcontract support of a laboratory-directed research and development (LDRD) project focusing on areas of both energy science and national security at the Idaho National Laboratory (INL), Idaho Falls, is gratefully acknowledged.

D. Subbaram Naidu, PhD, is Director, School of Engineering. Craig G. Rieger, PhD, is ICIS Distinctive Signature Lead.