加热炉燃烧系统先进控制策略的设计与实现

发布时间：2018-04-16 10:14

本文选题：加热炉 + 燃烧控制　；参考：《中国科学技术大学》2017年硕士论文

【摘要】：近年来我国钢铁行业持续低迷,钢铁企业竞争激烈。加热炉作为冶金工业中重要的能耗设备,其稳定、经济的运行是提高钢厂经济效益和竞争力的基础。但加热炉燃烧系统复杂,被控变量较多,常规控制策略常常难以达到满意的控制效果。为了提高加热炉的控制品质,有必要研究加热炉的先进控制策略。本文在分析加热炉燃烧系统特性的基础上,设计了加热炉先进控制策略,并在现场成功投运。投运后加热炉燃烧控制更加稳定,钢坯的氧化烧损量明显降低。在现场工作的基础上,本文提出了一种基于T-S模糊模型的加热炉炉温模糊预测控制策略,仿真结果表明了该策略的有效性。本文的主要工作内容和创新点如下:(1)设计了炉温的广义预测控制器,构建了炉温和流量的串级比值控制系统;提出了炉温和炉压的选择控制策略;设计了排烟温度PID控制器。设计先进控制软件以实现控制策略的计算、工艺指标的设定、被控变量的监测和控制方式的切换等。燃烧系统的先进控制策略在现场成功投运,投运效果显示该控制策略提高了加热炉的燃烧控制品质,降低了钢坯的氧化烧损率。(2)针对加热炉炉温对象具有一定非线性的特点,研究了基于输入输出数据的T-S模糊模型的建立方法。本文将边界混合约束的粒子群优化算法与模糊C-均值算法相结合,对T-S模型输入空间划分,采用最小二乘法辨识模型后件参数。仿真结果显示了该方法的有效性。(3)提出了一种基于加热炉历史数据的炉温模糊预测控制策略。基于加热炉历史数据建立炉温的T-S模糊模型,与广义预测控制算法相结合构成了模糊预测控制器。仿真结果显示,基于T-S模型的广义预测控制在全局范围内均具有良好的控制效果。
[Abstract]:In recent years, the iron and steel industry of our country continues to be depressed, iron and steel enterprises compete intensely.As an important energy consumption equipment in metallurgical industry, the stable and economical operation of reheating furnace is the basis to improve the economic efficiency and competitiveness of the steel plant.However, the combustion system of reheating furnace is complex and the controlled variables are many. The conventional control strategy is often difficult to achieve satisfactory control effect.In order to improve the control quality of reheating furnace, it is necessary to study the advanced control strategy of reheating furnace.Based on the analysis of the characteristics of the furnace combustion system, the advanced control strategy of the reheating furnace is designed and successfully put into operation in the field.After putting into operation, the combustion control of the furnace is more stable, and the amount of oxidation burning loss of the billet is obviously reduced.Based on the field work, a fuzzy predictive control strategy for furnace temperature based on T-S fuzzy model is proposed. The simulation results show the effectiveness of the strategy.The main contents and innovations of this paper are as follows: (1) the generalized predictive controller of furnace temperature is designed, the cascade ratio control system of furnace temperature and flow rate is constructed, the selection control strategy of furnace temperature and furnace pressure is put forward, and the PID controller of flue gas temperature is designed.The advanced control software is designed to realize the calculation of control strategy, the setting of process index, the monitoring of controlled variables and the switching of control mode.The advanced control strategy of the combustion system has been successfully put into operation on the spot. The effect of the operation shows that the control strategy improves the combustion control quality of the furnace and reduces the oxidation loss rate of the billet.The establishment of T-S fuzzy model based on input and output data is studied.In this paper, the particle swarm optimization algorithm with mixed boundary constraints is combined with the fuzzy C- mean algorithm. The input space of the T-S model is partitioned and the parameters of the model are identified by the least square method.Simulation results show the effectiveness of this method. (3) A fuzzy predictive control strategy for furnace temperature based on historical data of heating furnace is proposed.The T-S fuzzy model of furnace temperature is established based on the historical data of reheating furnace. The fuzzy predictive controller is constructed by combining with the generalized predictive control algorithm.The simulation results show that the generalized predictive control based on T-S model has good control effect in the global range.
【学位授予单位】：中国科学技术大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TG307;TP273

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