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Model Predictive Control Based on Fuzzy Linearizatio Technique For HVAC Systems Temperature Control

机译:基于模糊线性化技术的暖通空调系统模型预测控制。

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The heating, ventilating, and air-conditioning systems (HVAC systems) are typical nonlinear time-variable multivariate systems with disturbances and uncertainties. A new Mamdani fuzzy model predictive control strategy based on sum-min inference was proposed to control HVAC systems in this paper. The resolution relationship of two inputs and single output variables of the Mamdani fuzzy controller was obtained by its structure analysis. Then the fuzzy linearization predictive model at k+1 sampling time on base of its resolution equation was designed. And at P ahead horizon predictive models were got. The predictive control strategy based fuzzy linearization predictive model was given and the procedure to implement the control algorithm was outlined. Finally simulation test results showed that the proposed fuzzy model predictive control approach is effective in HVAC systems temperature control applications. Compared with the conventional PID control, this fuzzy model predictive control algorithm has less overshoot and shorter setting time
机译:加热,通风和空调系统(HVAC系统)是具有干扰和不确定性的典型非线性时变多元系统。提出了一种基于最小和推理的Mamdani模糊模型预测控制策略,以控制HVAC系统。通过对其结构进行分析,得到了Mamdani模糊控制器的两个输入和单个输出变量的分辨率关系。然后根据其分辨率方程,设计了在k + 1个采样时刻的模糊线性化预测模型。到了P点,就获得了地平线预测模型。给出了基于预测控制策略的模糊线性化预测模型,并概述了该控制算法的实现过程。最后的仿真测试结果表明,所提出的模糊模型预测控制方法在暖通空调系统温度控制应用中是有效的。与传统的PID控制相比,该模糊模型预测控制算法具有较少的过冲和较短的设置时间。

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