Thermal comfort is one of the most important factors of indoor environment quality, affecting occupants’ well-being and work efficiency. With the advent of smart control technology, personalized and intelligent air conditioners have been promoted for occupant-centric intelligent air-conditioning control. Based on commonly used air-conditioning (AC), this paper quantitatively describes the method for occupant thermal preference adaptation, and proposes a rule-based classification method of occupant thermal preference recognition. With the quantitative description and classification of the occupant thermal preference, this paper proposes a multi-step input control method for an occupant-centric fan-coil system. This method provides an indoor thermal environment that fulfills the demands of different preferences and is easy to implement with existing air-conditioning control systems without additional sensors. To perform an application-oriented, closed-loop research of the proposed control method, two prediction models of occupant thermal preferences are developed based on an occupant behavior dataset and they could be used as the well initialized models for future online tunning by continually accumulated dataset. Moreover, aiming for a practical operation guide for conventional occupant-centric air-conditioning systems, this paper validates the effectiveness and accuracy of the proposed multi-step input control method, integrated with occupant thermal preference recognition. This was done by using Programmable Logic Controller (PLC) control experiments and Simulink simulations of an actual personal office room, equipped with a fan-coil unit (FCU) in Shanghai. The research results indicate that dynamic indoor air temperature response with different air-conditioning control modes can meet the control needs of different occupant thermal preference patterns.

热舒适性是影响室内环境质量的最重要因素之一，它会影响居住者的健康和工作效率。随着智能控制技术的出现，个性化和智能化的空调已被推广到以乘员为中心的智能空调控制中。基于常用的空调技术，定量描述了乘员的热偏好适应方法，提出了一种基于规则的乘员的热偏好识别方法。通过对乘员热偏好的定量描述和分类，提出了一种以乘员为中心的风机盘管系统的多步输入控制方法。该方法提供了一种室内热环境，该环境可以满足不同偏好的需求，并且易于使用现有的空调控制系统来实现，而无需额外的传感器。为了对所提出的控制方法进行面向应用的闭环研究，基于乘员行为数据集，开发了两种乘员热偏好预测模型，它们可以用作不断初始化的数据集的良好初始化模型，用于将来的在线调教。此外，针对常规的以乘员为中心的空调系统的实用操作指南，本文验证了所提出的多步输入控制方法与乘员热偏好识别相结合的有效性和准确性。这是通过使用可编程逻辑控制器（PLC）控制实验和Simulink对实际的个人办公室进行模拟来完成的，该办公室在上海配备了风机盘管（FCU）。研究结果表明，采用不同空调控制模式的动态室内空气温度响应可以满足不同乘员热偏好模式的控制需求。