采用最优状态估计的主蒸汽温度动态矩阵控制方法
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摘要
针对主蒸汽温度控制系统不可测扰动影响的问题,提出一种基于最优状态估计的动态矩阵控制(OSEDMC)算法.首先分析主蒸汽温度系统的动态特性,归纳出减温水量对主蒸汽温度影响的数学模型;然后基于常规DMC算法,利用最优估计理论对DMC算法的预测序列进行补偿修正,有效抑制不可测扰动的影响,并提出一种Kalman滤波的降维算法,使其计算更加简洁、便于实际应用与在线计算. Simulink仿真结果表明:在不可测扰动影响下,所提出方法抑制扰动效果比常规DMC算法提高20%,抑制扰动能力有显著提升.
A method of dynamic matrix control based on optimal state estimation(OSE-DMC) is proposed for unmeasurable disturbances in a main steam temperature control system. Firstly, the dynamic characteristics and the mathematical model of main steam temperature with the disturbance of spray attemperator water are concluded based on the structure of the main steam temperature system. Then, a Kalman filter is designed to compensate the predictive sequence in the DMC algorithm according to the optimal state estimation theory. The influence of unmeasurable disturbance is effectively suppressed. In addition, a reduced-order algorithm for the Kalman filter is proposed to simplify calculation, which is convenient for practical application and on-line calculation. Simulation results show that the proposed method can increase the effect of disturbance suppression by 20 % compared with the conventional DMC algorithm, and the capability of disturbance suppression is significantly improved.
A method of dynamic matrix control based on optimal state estimation(OSE-DMC) is proposed for unmeasurable disturbances in a main steam temperature control system. Firstly, the dynamic characteristics and the mathematical model of main steam temperature with the disturbance of spray attemperator water are concluded based on the structure of the main steam temperature system. Then, a Kalman filter is designed to compensate the predictive sequence in the DMC algorithm according to the optimal state estimation theory. The influence of unmeasurable disturbance is effectively suppressed. In addition, a reduced-order algorithm for the Kalman filter is proposed to simplify calculation, which is convenient for practical application and on-line calculation. Simulation results show that the proposed method can increase the effect of disturbance suppression by 20 % compared with the conventional DMC algorithm, and the capability of disturbance suppression is significantly improved.
引文
[1]刘敏,张智,吴飞君,等.一台660 MW单元机组主蒸汽温度控制系统的设计与调试[J].现代电力, 2006, 2:60-63.(Liu M, Zhang Z, Wu F J, et al. The design and debuging of main steam temperature control system of 660 MW unit[J]. Modern Electric Power, 2006, 2:60-63.)
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[3]管志敏,林永君,王兵树,等.自抗扰控制器在火电厂主蒸汽温度控制中的仿真研究[J].热力发电, 2009,38(4):26-30.(Guan Z M, Lin Y J, Wang B S, et al. Simulation study of main steam temperature control of thermal power plant based on auto-disturbance rejector controller[J]. Thermal Power Generation, 2009, 38(4):26-30.)
[4]王勇.基于混沌粒子群的神经网络主汽温控制系统[J].计算机仿真, 2012, 29(8):322-325.(Wang Y. Main steam temperature control system based on CPSO and neural network[J]. Computer Simulation,2012, 29(8):322-325.)
[5]贾立,柴宗君.火电机组主蒸汽温度神经模糊-PID串级控制[J].控制工程, 2013, 20(5):877-881.(Jia L, Chai Z J. Neuro-fuzzy based PID cascade control of main steam temperature of fire electrical engineering set[J]. Control Engineering of China, 2013, 20(5):877-881.)
[6]程启明,王勇浩.基于Smith预估的模糊-PID串级主汽温控制系统仿真[J].电工技术学报, 2007, 3:143-147.(Cheng Q M, Wang Y H. Simulation study of fuzzy/PID cascade control system based on Smith predictive estimate on main steam temperature[J]. Trans of China Electrotechnical Society, 2013, 3:143-147.)
[7]竹瑞博,董泽,冉宁.自抗扰控制在火电厂主蒸汽温度控制中的应用[J].电力科学与工程, 2012, 28(5):46-49.(Zhu R B, Dong Z, Ran N. Application of active disturbance rejection control in main steam temperature control of thermal power plant[J]. Electric Power Science and Engineering, 2012, 28(5):46-49.)
[8]王国玉,韩璞,王东风.预测函数控制及其应用研究[J].系统仿真学报, 2002, 8:1087-1091.(Wang G Y, Han P, Wang D F. Predictive functional control and its application study[D]. J of System Simulation, 2002, 8:1087-1091.)
[9]孔小兵,范昌,刘向杰.超临界机组主汽温分布式监督预测控制[J].上海交通大学学报, 2017, 51(10):1252-1259.(Kong X B, Fan C, Liu X J. Distributed supervisory predictive control of main steam temperature for ultra-supercritical unit[J]. J of Shanghai Jiaotong University, 2017, 51(10):1252-1259.)
[10] Liu Xiangjie, Chan C W. Neuro-fuzzy generalized predictive control of boiler steam temperature[J]. IEEE Trans on Energy Conversion, 2006, 5(1):1027-1032.
[11]张华,沈胜强,郭慧彬.多模型分形切换预测控制在主汽温度调节中的应用[J].电机与控制学报, 2014,18(2):108-114.(Zhang H, Shen S Q, Guo H B. Application of multi-model fractal switching predictive control in main steam temperature[J]. Electric Machines and Control,2014, 18(2):108-114.)
[12]杨献勇.热工过程自动控制[M].北京:清华大学出版社, 2000:189.(Yang X Y. Automatic control of thermal process[M].Beijing:Tsinghua University Press, 2000:189.)
[13]谢亚军,丁宝苍,陈桥.动态矩阵控制中基于Kalman滤波的开环预测方法[J].控制与决策, 2017, 32(3):419-426.(Xie Y J, Ding B C, Chen Q. Open-loop prediction method in dynamic matrix control based on Kalman filter[J].Control and Decision, 2017, 32(3):419-426.)
[2]王沛然.主汽温新型控制系统设计与研究[D].北京:华北电力大学控制与计算机工程学院, 2005.(Wang P R. Study on the application of main stream temperature control system based on auto disturbance rejection technique[D]. Beijing:School of Control and Computer Engineering, North China Electric Power University, 2005.)
[3]管志敏,林永君,王兵树,等.自抗扰控制器在火电厂主蒸汽温度控制中的仿真研究[J].热力发电, 2009,38(4):26-30.(Guan Z M, Lin Y J, Wang B S, et al. Simulation study of main steam temperature control of thermal power plant based on auto-disturbance rejector controller[J]. Thermal Power Generation, 2009, 38(4):26-30.)
[4]王勇.基于混沌粒子群的神经网络主汽温控制系统[J].计算机仿真, 2012, 29(8):322-325.(Wang Y. Main steam temperature control system based on CPSO and neural network[J]. Computer Simulation,2012, 29(8):322-325.)
[5]贾立,柴宗君.火电机组主蒸汽温度神经模糊-PID串级控制[J].控制工程, 2013, 20(5):877-881.(Jia L, Chai Z J. Neuro-fuzzy based PID cascade control of main steam temperature of fire electrical engineering set[J]. Control Engineering of China, 2013, 20(5):877-881.)
[6]程启明,王勇浩.基于Smith预估的模糊-PID串级主汽温控制系统仿真[J].电工技术学报, 2007, 3:143-147.(Cheng Q M, Wang Y H. Simulation study of fuzzy/PID cascade control system based on Smith predictive estimate on main steam temperature[J]. Trans of China Electrotechnical Society, 2013, 3:143-147.)
[7]竹瑞博,董泽,冉宁.自抗扰控制在火电厂主蒸汽温度控制中的应用[J].电力科学与工程, 2012, 28(5):46-49.(Zhu R B, Dong Z, Ran N. Application of active disturbance rejection control in main steam temperature control of thermal power plant[J]. Electric Power Science and Engineering, 2012, 28(5):46-49.)
[8]王国玉,韩璞,王东风.预测函数控制及其应用研究[J].系统仿真学报, 2002, 8:1087-1091.(Wang G Y, Han P, Wang D F. Predictive functional control and its application study[D]. J of System Simulation, 2002, 8:1087-1091.)
[9]孔小兵,范昌,刘向杰.超临界机组主汽温分布式监督预测控制[J].上海交通大学学报, 2017, 51(10):1252-1259.(Kong X B, Fan C, Liu X J. Distributed supervisory predictive control of main steam temperature for ultra-supercritical unit[J]. J of Shanghai Jiaotong University, 2017, 51(10):1252-1259.)
[10] Liu Xiangjie, Chan C W. Neuro-fuzzy generalized predictive control of boiler steam temperature[J]. IEEE Trans on Energy Conversion, 2006, 5(1):1027-1032.
[11]张华,沈胜强,郭慧彬.多模型分形切换预测控制在主汽温度调节中的应用[J].电机与控制学报, 2014,18(2):108-114.(Zhang H, Shen S Q, Guo H B. Application of multi-model fractal switching predictive control in main steam temperature[J]. Electric Machines and Control,2014, 18(2):108-114.)
[12]杨献勇.热工过程自动控制[M].北京:清华大学出版社, 2000:189.(Yang X Y. Automatic control of thermal process[M].Beijing:Tsinghua University Press, 2000:189.)
[13]谢亚军,丁宝苍,陈桥.动态矩阵控制中基于Kalman滤波的开环预测方法[J].控制与决策, 2017, 32(3):419-426.(Xie Y J, Ding B C, Chen Q. Open-loop prediction method in dynamic matrix control based on Kalman filter[J].Control and Decision, 2017, 32(3):419-426.)