在商业建筑中广泛采用楼宇自动化系统（BAS）的一个巨大障碍是其复杂、耗时且通常是专有的安装、配置和调试过程。本研究提出了一个即插即用暖通空调空气处理机组（AHU）控制系统的框架。这是一个即插即用的暖通空调控制系统的基础和第一步，这将最终导致自动配置的空调控制系统用于自动BAS设置、配置、调试以及可能的自动检测和修复潜在的控制问题。 该框架基于与IEEE 1451标准系列兼容的商用智能传感器。为了解决解决系统模糊性的关键问题，开发了一种结构模式识别算法来自动识别AHU中的温度传感器位置。该算法可以是即插即用或自配置HVAC控制系统的关键部分，用于建立控制系统输入/输出的绑定列表，并自动分配和验证绑定列表。 这项工作由两部分组成。本论文第一部分回顾了现有技术，并讨论了将即插即用和自配置概念纳入暖通空调控制系统的技术差距。然后提出了AHU的即插即用框架。第二部分（Zhou和Nelson 2011）是一篇配套论文，它开发了一种结构模式识别算法，用于自动识别AHU温度传感器的位置，并提出了一种解决AHU系统模糊性的方案。插头的原型- AHU的play框架是在一个实验设施中构建和测试的。在各种初始条件、环境温度和冷冻水系统配置下进行测试，以证明框架的可行性和模式识别算法的鲁棒性。引文:ASHRAE Transactions，第117卷，第2部分，魁北克省蒙特利尔

A huge barrier to wider adoption of building automation systems (BAS) in commercial buildings is their complex, timeconsuming, and often proprietary installation, configuration, and commissioning process. A framework for plug-and-play HVAC air-handling unit (AHU) control systems is proposed in this study. This is the foundation and the first step toward a plug-and-play HVAC control system that will eventually lead to self-configuring HVAC control systems for automatic BAS setup, configuration, commissioning, and possible automatic detection and repair of potential controls problems. This framework is built on commercially available smart transducers that are compatible with the IEEE 1451 family of standards. To solve the critical issue of resolving system ambiguity, a structural pattern recognition algorithm is developed to automatically recognize temperature sensor locations in an AHU. The algorithm can be a critical part of a plug-and-play or selfconfiguring HVAC control system in establishing a binding list of control system input/output and automated assignment and verification of the binding list. This work consists of two parts. Part I, the present paper, reviews existing technologies and discusses technology gaps for incorporating plug-and-play and self-configuring concepts into HVAC control systems. A plug-and-play framework for an AHU is then proposed. Part II (Zhou and Nelson 2011), a companion paper, develops a structural pattern recognition algorithm to automatically identify AHU temperature sensor locations and a scheme to resolve AHU system ambiguity. A prototype of the plug-and-play framework for an AHU was built and tested in an experimental facility. Tests are conducted at various initial conditions, environmental temperatures, and chilled-water system configurations to demonstrate the feasibility of the framework and the robustness of the pattern recognition algorithm.