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集中供热系统是1个复杂的多输入多输出系统,具有非线性、强耦合、时变和大滞后等特点,采用经典控制理论和现代控制理论很难在保证供热质量的前提下,实现节能、减排的优化控制目标。自适应动态规划(ADP)是人工智能和控制学科发展交汇的新方法,提出了解决大规模复杂非线性系统优化控制问题的方法。在分析集中供热系统运行机理的基础上,建立热源总热量生产优化问题的数学描述,利用双启发式动态规划(DHP)算法和质量并调的控制策略求解,获得热源供水流量和供水温度的优化设定值。仿真结果表明,此方法可以实现热源处总热量生产问题的优化控制,并能求出其相应的供水温度和供水流量的最优控制量,达到供需匹配和节能降耗的目的。
The central heating system is a complex multi-input and multi-output system with characteristics of non-linearity, strong coupling, time-varying and large hysteresis. It is difficult to realize the heating quality by using the classical control theory and the modern control theory Energy saving, emission reduction optimization control objectives. Adaptive Dynamic Programming (ADP) is a new method for the intersection of artificial intelligence and control disciplines. A method to solve the optimization control problem of large-scale complex nonlinear systems is proposed. Based on the analysis of the operating mechanism of central heating system, a mathematic description of heat source total heat production optimization problem is established. By using DHT algorithm and quality control strategy, the heat source water supply flow rate and water supply temperature Optimize settings. The simulation results show that this method can realize the optimal control of the total heat production at the heat source, and can find out the optimal control quantity of the corresponding water supply temperature and water supply flow to meet the supply and demand matching and energy saving.