烟气脱硫智能控制系统研究

详细信息    查看全文 | 推荐本文 |

英文篇名：Research on intelligent control system of flue gas desulfurization 作者：梁克顺 ; 马立新 ; 郭玲妹 英文作者：LIANG Keshun;MA Lixin;GUO Lingmei;School of Optical-Electrical and Computer Engineering, University of Shanghai for Science & Technology; 关键词：烟气脱硫 ; Smith预估 ; 自适应 ; 抗干扰 ; 精准模型 英文关键词：flue gas desulfurization;;Smith predictive;;adaptive;;anti-interference;;precise model 中文刊名：DLQB 英文刊名：Electric Power Science and Engineering 机构：上海理工大学光电信息与计算机工程学院; 出版日期：2019-04-28 出版单位：电力科学与工程 年：2019 期：v.35;No.228 语种：中文; 页：DLQB201904009 页数：5 CN：04 ISSN：13-1328/TK 分类号：63-67

摘要

目前,在我国能源结构中,火力发电投入的比例很大,故此控制SO_2的排放尤为重要。烟气脱硫控制系统具有时变、滞后大、非线性和大惯性的特点,大滞后性问题可以利用Smith预估控制方案来解决。但传统的Smith控制器需要精准的模型才能得到较好的效果。但在脱硫系统往往无法提供精准的模型。在此基础上,提出了自适应Smith预估器烟气脱硫控制模型,并用MATLAB进行了仿真。结果表明,自适应Smith控制器在烟气脱硫控制系统中有较好的效果,明显提高了其抗干扰性能,使系统具有了良好的鲁棒性,缩短了调节时间,降低了超调量。
        At present, in China's energy structure, the proportion of investment in thermal power generation is very large, so it is particularly important to control the emission of SO_2. The flue gas desulphurization control system is characterized by time-varying, large hysteresis, non-linearity and large inertia. However, traditional Smith controller requires accurate model to achieve better results. But in the desulphurization system, it is impossible to provide accurate model. In view of this situation, an adaptive Smith estimator flue gas desulphurization control model was proposed in this paper and simulated in MATLAB. The results show that the adaptive Smith controller has a good effect in the flue gas desulphurization control system, which obviously improves its anti-interference performance, makes the system have good robustness, shortens the adjustment time and reduces the overdose.

引文

[1]袁淑娟,原晓琴,马立新,等.预估模型的烟气氨法脱硫控制系统[J].控制工程,2017,24(1):178-182.
    [2]武春锦,吕武华,梅毅,等.湿法烟气脱硫技术及运行经济性分析[J].化工进展,2015,34(12):4368-4374.
    [3]松村司郎,平山开一郎,马立新.发电设备中的控制技术[M].北京:机械工业出版社,2012:31-45.
    [4]王永帅,陈增强,孙明玮,等.一阶惯性大时滞系统Smith预估自抗扰控制[J/OL].智能系统学报,2018,13(4):500-508.
    [5]HASHEMI M,ASKARI J,GHAISARI J,et al.Robust adaptive actuator failure compensation for a class of uncertain nonlinear systems[J].International Journal of Automation and Computing,2017(6):85-94.
    [6]张毅超,白建云.一种改进型Smith预估补偿控制算法及其应用[J].自动化技术与应用,2016,35(10):1-3.
    [7]李杰,齐晓慧,刘新海,等.改进模型参考自适应控制及其在解耦控制中的应用[J].电机与控制学报,2015,19(5):112-120.
    [8]佘致廷,秦亚胜,杨婷,等.基于模型参考自适应的单神经元PID控制器设计[J].电力电子技术,2016,50(5):89-92.
    [9]刘长良,马增辉.过热汽温系统的Smith预估器参数多目标优化控制[J].模式识别与人工智能,2015,28(3):282-288.
    [10]王玉华,郑骁健.基于模型参考模糊自适应PID的高压釜温度控制[J].自动化仪表,2017,38(5):45-49.
    [11]王欣峰,任淑萍.一种火力发电厂烟气脱硫控制方法研究仿真[J].计算机仿真,2016,33(12):148-151.
    [12]GIRALDO S A C,FLESCH R C C,NORMEY-RICO J E.Multivariable greenhouse control using the filtered smith predictor[J].Journal of Control,Automation and Electrical Systems,2016,27(4):349-358.
    [13]伏甲琪,郭为民,刘延泉,等.Smith预估滑模控制在时滞系统中的应用[J].仪器仪表用户,2016,23(10):66-67.
    [14]徐星星,张春,何慧云,等.基于改进Smith预估时延补偿的GPC网络控制系统研究[J].南阳师范学院学报,2016,15(9):39-43.