Optimal tuning of cascaded control architectures for nonlinear HVAC systems. (17th November 2017)

• Record Type: Journal Article
• Authors: Price, Christopher; Rasmussen, Bryan P.
• Is Part Of: Science and technology for the built environment. Volume 23:Number 8(2017)
• Page Start: 1190
• Page End: 1202
• Publication Date: 2017-11-17
• Subjects: Heating -- Periodicals; Ventilation -- Periodicals; Air conditioning -- Periodicals; Refrigeration and refrigerating machinery -- Periodicals; Indoor air quality -- Periodicals; Indoor air quality; Air conditioning; Heating; Refrigeration and refrigerating machinery; Ventilation; Periodicals; 697
• DOI: 10.1080/23744731.2016.1262663
• Languages: English
• ISSNs: 2374-474X

Abstract

Abstract : Cascaded controllers have been shown in recent literature to significantly reduce hunting behavior and improve the performance of a variety of HVAC systems. The cascaded architecture uses multiple proportional-integral-derivative loops, standard in industry and building automation controls, to minimize the effects of load dependent nonlinearities. This article builds on previous work by defining and demonstrating the properties of two nonlinear gap metrics that quantify the closed-loop linearization of the cascaded control structure and enable proper tuning of the inner-loop proportional gain. This is followed by the development of a linear quadratic framework that enables simultaneous tuning of inner- and outer-loop control gains. The proposed gap metrics and tuning procedures are demonstrated with two case studies. A simple single input, two output example plant is used to demonstrate the benefits of the proposed tuning method compared to standard proportional-integral-derivative control and successive loop closure tuning techniques. The tuning approach is also applied to the control of a two-ton, residential heat pump system. The proposed metrics and tuning techniques showed significant improvement in control over standard proportional-integral-derivative control tuning methods in both simulation and experiment.