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集中供热系统存在大惯性、非线性以及时变性等问题,为了保证集中供热系统末端用户的采暖质量,针对集中供热二次网系统,设计了二次网回水温度的预测模型及智能控制策略,以实现二次网回水温度的准确控制,满足末端用户的采暖需求。通过飞升曲线建立了温控系统的数学模型。设计了一个RBF神经网络预测模型,模型的输出作为温控系统的二次网回水温度给定值。在控制算法上,设计了三层前向型神经网络与PID相结合的智能控制器,实现对二次网回水温度的闭环控制。基于所建立的数学模型、预测模型及控制器进行了仿真实验。仿真结果表明,所采用的控制方法与常规PID控制相比,具有调节时间短,超调量小的优点。验证了所采用控制方法的可行性和有效性。
In order to ensure the heating quality of the end users of central heating system, central heating system has the problems of large inertia, non-linearity and time-varying degeneration. For the secondary heating central heating system, the prediction model and intelligence of secondary network backwater temperature are designed Control strategy, in order to achieve accurate control of the secondary network backwater temperature to meet the end-user heating needs. The mathematical model of temperature control system is established by the soaring curve. A RBF neural network prediction model is designed. The output of the model is used as the secondary network backwater temperature reference for the temperature control system. In the control algorithm, an intelligent controller combining three-layer forward neural network and PID is designed to realize the closed-loop control of the secondary network return water temperature. Based on the established mathematical model, the predictive model and the controller are simulated. Simulation results show that compared with the conventional PID control, the control method has the advantages of short adjustment time and small overshoot. Verify the feasibility and effectiveness of the control method adopted.