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Optimal control of HVAC systems using DDP and NLP techniques
Author(s) -
Kota Narendra N.,
House John M.,
Arora Jasbir S.,
Smith Theodore F.
Publication year - 1996
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/(sici)1099-1514(199601/03)17:1<71::aid-oca561>3.0.co;2-e
Subject(s) - hvac , computer science , dynamic programming , optimal control , quadratic programming , artificial intelligence , mathematical optimization , machine learning , algorithm , air conditioning , mathematics , engineering , mechanical engineering
Abstract The objective of this study is to apply the differential dynamic programming (DDP) technique of optimal control to heating, ventilating and air‐conditioning (HVAC) systems and to compare its performance with a non‐linear programming (NLP) technique using the sequential quadratic programming method. The DDP technique is briefly described and studied. Limitations of the technique are noted. Three cases of a system that has been treated previously in the literature are optimized by the two techniques and the computational times compared. The study shows DDP to be efficient compared with NLP for the example problems. NLP is, however, more robust and general and can treat constraints on the state variables directly. Further investigation is needed for larger‐scale problems to fully explore the features of the two methods.