供热过程中高效热量控制方法的研究与仿真

Research and Simulation on Efficient Method for Heat Control in Heating Supply Process

研究供热系统优化控制问题,由于集中供热控制系统大都采用PID控制算法,一旦外部供热要求在时间上频率小幅度高,会导致PID控制无法适应供热对象的变化,大幅改变参数。传统控制过程具有滞后性和时变性,效率下降。为解决上述问题,提出一种预测神经网络的自适应PID热量控制方法,对集中供热系统的热量调控参数进行分析后,采用自适应PID控制方法对调控参数进行控制,通过预测神经网络对参数偏差进行提前预测,及时调整相关参数值,加快系统的响应速度,有效抑制外部变化扰动因素,实现对供热系统热量的准确控制。仿真结果表明,改进方法的对热量的控制能力优于传统方法,并且具有较强的自适应能力和抗干扰能力。

The optimal control of heating supply system was studied in this paper. At present, the current central heating control systems mostly adopt PID control algorithm, once the frequency of the external heating requirements increase , which will lead to PID control cant adapt to the changing of the heating object and change the parameters sharply. Traditional control process has the characteristics like hysteresis, time - varying resulting inefficient. In or- der to solve the above problems, a self - adaptive PID method for heat control is proposed based on a prediction of the neural network. In this method, after the analysis of heat regulation parameter of central heating system, self- adap- tive PID control method is used to control the regulation parameter. Through the prediction neural network, the devia- tion of parameters can be predicted in advance, and the value of relevant parameters can be adjusted on time, so as to speed up the response speed of system, effectively inhibit the external change disturbance factors, and realize the accurate control of the heating system. Simulation experimental results show that the ability of this method for heat control is superior to traditional methods, and has strong adaptive ability and anti - interference ability.