ASHRAE IJHVAC 15-6-2009 HVAC&R Research《《HVAC&R研究》》.pdf
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1、 VOLUME 15, NUMBER 6 HVAC accepted May 27, 2009While the dynamics of most HVAC Dexter and Haves 1989). Techniques for robust PID control design have also been suggested based on modern controltheory (e.g., Noda et al. 2003). While potentially effective, the complexity of the underlyingtheory means t
2、hat the majority of users may be unaware of the subtleties or the possible pitfallsof such approaches. Although the potential of these advanced control strategies to increase HVAC ASHRAE 2005; USDOE 2001), in general the industry has not yet enthusiasticallyadopted the strategies (Brambley et al. 20
3、05), and commercially available adaptive, predictive,and robust controllers comprise a minority of the controllers in operation. Fixed PID controllerscontinue to make up the bulk of commercial HVAC the reader is referred to the appendix for definitionsof essential terminology. 2009, American Society
4、 of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in HVAC Finn and Doyle 2000;Outtagarts et al. 1997). This approach attempts to capture the dynamic response of the systemin question in terms of a constant gain k0, a first-order time constant , and time dela
5、y Td, asshown in the following transfer function:(1)To simplify the analysis, a Pad approximation of the time delay may be used to obtain a lin-ear transfer function (Franklin et al. 2006). For example, a first-order Pad approximationresults in the following transfer function: (2)For systems with de
6、lays that are small relative to the dominant time constant, this simple sub-stitution leads to a close approximation of the open-loop behavior of the system. A majority of HVAC ODwyer 2006). These tuning approaches require either an explicit modelfor the system or data from simple experiments, such
7、as an impulse or step-response test. Forexample, the Ziegler-Nichols tuning method presented in most introductory control textbooks(Franklin et al. 2006) involves applying a proportional control to the system and increasing thecontroller gain until the systems step response borders on instability. O
8、ne can then calculate thePID control gains using the values for the period of oscillations and the critical control gain.Other approaches identify a simple model of the transient response and then design the PID con-troller using classical model-based approaches (e.g., Root-Locus, frequency domain d
9、esign,etc.) (Franklin et al. 2006). These techniques, whether empirical or model based, inherently focus on tuning a controllerfor a single operating condition. This is in contrast with the techniques presented in this paper,which have the unique capability of being able to simultaneously address st
10、ability and perfor-mance of an HVAC however, recent advances in control theory overcomemany of these challenges, allowing users to define a set of linear inequalities that define the sta-bilizing range of PID controller gains and, to some extent, the range of PID gains that meet spec-ified transient
11、 performance characteristics. In essence, the final objective of these techniques is to provide the control designer with simplefigures (e.g., Figure 1 or 5) that denote the range of PID control gains that stabilize the given sys-Figure 1. Example figure of stabilizing control gains and meeting sett
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