Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

被引：13
|
作者：
Lü H. [1 ]
Jia L. [1 ]
Kong S. [2 ]
Zhang Z. [2 ]
机构：
[1] School of Control Science and Engineering, Shandong University, Jinan
[2] School of Mathematics Science, Qufu Normal University, Qufu
来源：
Journal of Control Theory and Applications | 2007年 / 5卷 / 1期
关键词：
HVAC systems; Least squares method; Predictive functional control; T-S fuzzy model;
D O I：
10.1007/s11768-005-5301-7
中图分类号：
学科分类号：
摘要：
In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc. © Editorial Board of Control Theory & Applications 2007.
引用
收藏
页码：94 / 98
页数：4
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