针对过热汽温控制的自适应预测控制器设计
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摘要
针对火电厂过热蒸汽温度控制这种具有大延迟、大惯性、非线性、强时变性等特性的被控对象,设计针对火电厂过热蒸汽温度控制的自适应模型预测控制器,通过对不同模型的在线辨识和控制表明,采用自适应模型预测控制器对过热蒸汽温度进行调节,效果较普通模型预测控制器相比,调节时间大幅缩短,超调量得到了减小或消除,动态性能有了较大的改善。结果表明,该自适应模型预测控制器实施手段简便,可在电厂推广使用,也可应用到解决同类问题中去,具有广阔的应用前景。
An adaptive model predictive controller for overheating steam temperature control of thermal power plants is designed, which is based on the control object with large delay, large inertia, nonlinearity and strong time-varying properties. Through the on-line identification and control of different models,compared with predictive controllers in a general model, in terms of adjusting the superheat steam temperature, the adjusting time can be shortened drastically, the overshoot can be reduced or even eliminated, and the dynamic performance is improved greatly when applying in adaptive model predictive controller. The results show that the adaptive model predictive controller, because of its simple implementation, can be used in power plants, and also can be applied to solve similar problems, which has a broad application prospects.
An adaptive model predictive controller for overheating steam temperature control of thermal power plants is designed, which is based on the control object with large delay, large inertia, nonlinearity and strong time-varying properties. Through the on-line identification and control of different models,compared with predictive controllers in a general model, in terms of adjusting the superheat steam temperature, the adjusting time can be shortened drastically, the overshoot can be reduced or even eliminated, and the dynamic performance is improved greatly when applying in adaptive model predictive controller. The results show that the adaptive model predictive controller, because of its simple implementation, can be used in power plants, and also can be applied to solve similar problems, which has a broad application prospects.
引文
[1]李佳.模糊自整定PID控制在过热汽温控制系统中的研究与应用[D].哈尔滨:哈尔滨理工大学,2012.Li Jia.Study and Application of the Fuzzy Self-tuning PID Control in Superheated Steam Temperature System[D].Harbin:Harbin University of Science and Technology,2012.
[2]田伟.基于非线性状态观测器的过热汽温控制系统的分析与设计[D].石家庄:华北电力大学,2013.Tian Wei.The Analysis and Design of Superheated Steam Temperature Control System Based on Nonlinear State Observer[D].Shijiazhuang:North China Electric Power University,2013.
[3]张丽香,陈凤兰.自适应Smith预估补偿的过热汽温控制系统[J].信息与控制,2015,44(5):513-518.Zhang Lixiang,Chen Fenglan.Superheated Steam Temperature Control System Based on Adaptive Smith Predictive Compensation[J].Information and Control,2015,44(5):513-518.
[4]刘长良,马增辉,开平安.电站过热汽温系统的内模PID控制及其仿真[J].系统仿真学报,2014,26(11):2722-2733.Liu Changliang,Ma Zenghui,Kai Ping’an.Inter Model PID Control and Its Simulation in Main Steam Temperature System of Power Plant[J].Journal of System Simulation,2014,26(11):2722-2733.
[5]吴丹丹,张丽香,王俊刚.基于TDFMD PID的锅炉过热汽温控制系统研究[J].动力工程学报,2015,35(12):970-974.Wu Dandan,Zhang Lixiang,Wang Jungang.Study on Bolier Superheated Steam Temperature Control System Based on TDFMD PID[J].Journal of Chinese Society of Power Engineering,2015,35(12):970-974.
[6]孙立,董君伊,李东海.基于果蝇算法的过热汽温自抗扰优化控制[J].清华大学学报(自然科学版),2014,54(10):1288-1292.Sun Li,Dong Junyi,Li Donghai.Active disturbance rejection control for superheated steam boiler temperatures using the fruit fly algorithm[J].Journal of Tsinghua University(Science and Technology),2014,54(10):1288-1292.
[7]王富强.基于逆向传递策略的直流锅炉主汽温网络化预测控制[J].中国电机工程学报,2015,35(19):4981-4990.Wang Fuqiang.Networked Predictive Control of Main Steam Temperature for Once-through Boiler Based on Reverse Transfer Strategy[J].Proceedings of the CSEE,2015,35(19):4981-4990.
[8]钱积新,赵均,徐祖华.预测控制[M].1版.北京:化学工业出版社,2007:49-68.Qian Jixin,Zhao Jun,Xu Zuhua.Predictive control[M].1st ed.Beijing:Chemical Industry Press,2007:49-68.
[9]王杰,姜国强,王栓.基于混合学习算法的RBF神经网络主蒸汽温度控制[J].热力发电,2009,38(2):28-32.Wang Jie,Jiang Guoqiang,Wang Shuan.Main Steam temperature Control Using RBF Neural Network Based on Hybrid Learning Algorithm[J].Thermal Power Generation,2009,38(2):28-32.
[10]张波.串级模糊控制器自过热蒸汽温度控制中的应用[J].锅炉技术,2010,41(2):5-9.Zhang Bo.The Cascade Fuzzy Controller in the Application of the Superheat Vapor Temperature[J].Boiler Technology,2010,41(2):5-9.
[11]濮卫兴,陈来九.用B样条神经网络设计自适应模糊控制器[J].控制理论与应用,1996,13(4):448-454.Pu Weixing,Chen Laijiu.Designing Adaptive Fuzzy Controllers Based on B-Spline Neural Networks[J].Control Theory&Applications,1996,13(4):448-454.
[12]王喜庆,冯晓露.电厂过热蒸汽温度的有约束预测控制[J].动力工程学报,2010,30(3):192-195.Wang Xiqing,Feng Xiaolu.Application of Constrained Predictive Model to Power Plant Superheated Steam Temperature Control[J].Journal of Chinese Society of Power Engineering,2010,30(3):192-195.
[13]杨祖魁.基于模型技术的典型低氮燃烧型AGC机组控制系统优化[D].上海:上海电力学院,2016.Yang Zukui.Control System Optimization of Typical Low Nitrogen Combustion AGC Unit Based on Model Technology[D].Shanghai:Shanghai University of Electric Power,2016.
[14]王谦.基于继电反馈的预测PI控制系统性能评价[D].沈阳:沈阳工业大学,2008.Wang Qian.Performance Assessment to Predictive PIControl System Based on Relay Feedback[D].Shenyang:Shenyang University of Technology,2008.
[2]田伟.基于非线性状态观测器的过热汽温控制系统的分析与设计[D].石家庄:华北电力大学,2013.Tian Wei.The Analysis and Design of Superheated Steam Temperature Control System Based on Nonlinear State Observer[D].Shijiazhuang:North China Electric Power University,2013.
[3]张丽香,陈凤兰.自适应Smith预估补偿的过热汽温控制系统[J].信息与控制,2015,44(5):513-518.Zhang Lixiang,Chen Fenglan.Superheated Steam Temperature Control System Based on Adaptive Smith Predictive Compensation[J].Information and Control,2015,44(5):513-518.
[4]刘长良,马增辉,开平安.电站过热汽温系统的内模PID控制及其仿真[J].系统仿真学报,2014,26(11):2722-2733.Liu Changliang,Ma Zenghui,Kai Ping’an.Inter Model PID Control and Its Simulation in Main Steam Temperature System of Power Plant[J].Journal of System Simulation,2014,26(11):2722-2733.
[5]吴丹丹,张丽香,王俊刚.基于TDFMD PID的锅炉过热汽温控制系统研究[J].动力工程学报,2015,35(12):970-974.Wu Dandan,Zhang Lixiang,Wang Jungang.Study on Bolier Superheated Steam Temperature Control System Based on TDFMD PID[J].Journal of Chinese Society of Power Engineering,2015,35(12):970-974.
[6]孙立,董君伊,李东海.基于果蝇算法的过热汽温自抗扰优化控制[J].清华大学学报(自然科学版),2014,54(10):1288-1292.Sun Li,Dong Junyi,Li Donghai.Active disturbance rejection control for superheated steam boiler temperatures using the fruit fly algorithm[J].Journal of Tsinghua University(Science and Technology),2014,54(10):1288-1292.
[7]王富强.基于逆向传递策略的直流锅炉主汽温网络化预测控制[J].中国电机工程学报,2015,35(19):4981-4990.Wang Fuqiang.Networked Predictive Control of Main Steam Temperature for Once-through Boiler Based on Reverse Transfer Strategy[J].Proceedings of the CSEE,2015,35(19):4981-4990.
[8]钱积新,赵均,徐祖华.预测控制[M].1版.北京:化学工业出版社,2007:49-68.Qian Jixin,Zhao Jun,Xu Zuhua.Predictive control[M].1st ed.Beijing:Chemical Industry Press,2007:49-68.
[9]王杰,姜国强,王栓.基于混合学习算法的RBF神经网络主蒸汽温度控制[J].热力发电,2009,38(2):28-32.Wang Jie,Jiang Guoqiang,Wang Shuan.Main Steam temperature Control Using RBF Neural Network Based on Hybrid Learning Algorithm[J].Thermal Power Generation,2009,38(2):28-32.
[10]张波.串级模糊控制器自过热蒸汽温度控制中的应用[J].锅炉技术,2010,41(2):5-9.Zhang Bo.The Cascade Fuzzy Controller in the Application of the Superheat Vapor Temperature[J].Boiler Technology,2010,41(2):5-9.
[11]濮卫兴,陈来九.用B样条神经网络设计自适应模糊控制器[J].控制理论与应用,1996,13(4):448-454.Pu Weixing,Chen Laijiu.Designing Adaptive Fuzzy Controllers Based on B-Spline Neural Networks[J].Control Theory&Applications,1996,13(4):448-454.
[12]王喜庆,冯晓露.电厂过热蒸汽温度的有约束预测控制[J].动力工程学报,2010,30(3):192-195.Wang Xiqing,Feng Xiaolu.Application of Constrained Predictive Model to Power Plant Superheated Steam Temperature Control[J].Journal of Chinese Society of Power Engineering,2010,30(3):192-195.
[13]杨祖魁.基于模型技术的典型低氮燃烧型AGC机组控制系统优化[D].上海:上海电力学院,2016.Yang Zukui.Control System Optimization of Typical Low Nitrogen Combustion AGC Unit Based on Model Technology[D].Shanghai:Shanghai University of Electric Power,2016.
[14]王谦.基于继电反馈的预测PI控制系统性能评价[D].沈阳:沈阳工业大学,2008.Wang Qian.Performance Assessment to Predictive PIControl System Based on Relay Feedback[D].Shenyang:Shenyang University of Technology,2008.