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

机译:基于模糊T-S模型的HVAC系统温度控制预测功能控制

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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.
机译:在供暖,通风和空调(HVAC)系统中,存在严重的非线性,时变性质,干扰和不确定性。提出了一种基于Takagi-Sugeno(T-S)模糊模型的新型预测功能控制系统来控制HVAC系统。采用最小二乘方法得到了稳定控制过程的T-S模糊模型,然后在T-S模糊模型的全局线性预测模型的基础上,由预测功能控制器对过程进行控制。特别是开发了反馈调节部分来补偿模糊预测模型的不确定性。最后,在空调系统控制应用中的仿真测试结果表明,所提出的模糊模型预测功能控制提高了跟踪效果和鲁棒性。与传统的PID控制器相比,该控制策略具有减少过冲和缩短设置时间等优点。

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