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对于热水温度的高精度控制,传统采用的单级蒸汽压缩式循环控制算法存在温度控制适应性差、调节效果不理想的问题。基于神经网络PID控制算法的热水温度的高精度控制方法可以有效解决上述问题。该算法采用模糊控制规则对PID参数进行修改,融合RBF神经网络辨识器实现温度控制系统的Jacobian矩阵信息在线辨识,使RBF-PID控制器控制参数在线自整定,进而达到了复叠式建筑中热泵的热水温度的高精度控制目的。实验仿真证明,基于神经网络PID控制算法的热水温度的高精度控制方法适应性强,控制效率高,节能效果好。
For high-precision control of hot water temperature, the traditional single-stage vapor compression cycle control algorithm has poor adaptability to temperature control and poor regulation effect. The high precision control method of hot water temperature based on neural network PID control algorithm can effectively solve the above problems. The algorithm uses fuzzy control rules to modify the PID parameters, integrates the RBF neural network identifier to recognize the Jacobian matrix information of the temperature control system online, and makes the control parameters of the RBF-PID controller self-tuning online, The hot water temperature of high precision control purposes. The experimental simulation proves that the high precision control method of hot water temperature based on neural network PID control algorithm has strong adaptability, high control efficiency and good energy saving effect.