运用灰色预测与模糊加权PID的反应釜温度控制
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摘要
为了克服反应釜温度控制的滞后性以及弱跟随性问题,并提高温度控制精度和控制效果,在传统PID算法中加入比例设定值权重,在此基础上加入模糊控制,通过模糊规则在线调整加权PID的比例系数和比例设定值权重,以此来加强温度控制的跟随性。在反馈回路中加入灰色预测模型,通过对未来时刻温度进行预测而给出超前的控制作用,以此来削弱反应釜的滞后性。结果表明:该控制方式相比传统PID控制具有更好的响应速度和稳态精度,并且超调量更小。最终应用于油墨反应温度控制中,控制效果得到了明显的改善。
In order to overcome the hysteresis and weak following ability of temperature control in reactor and improve the temperature control accuracy and control effect,in the traditional PID algorithm the weight in the proportional set value was added. On this basis,the fuzzy control was added,and the weighted PID proportional coefficient and the proportional set value weight were adjusted online by the fuzzy rule to enhance the temperature followability. A gray prediction model was added to the feedback loop to give an advanced control effect by predicting the temperature at a future time,thereby weakening the hysteresis of the reactor. The results show that this control method has better response speed and steady-state accuracy than the conventional PID control,and the overshoot is smaller. Finally,it is applied to the ink reaction temperature control,and the control effect is obviously improved.
In order to overcome the hysteresis and weak following ability of temperature control in reactor and improve the temperature control accuracy and control effect,in the traditional PID algorithm the weight in the proportional set value was added. On this basis,the fuzzy control was added,and the weighted PID proportional coefficient and the proportional set value weight were adjusted online by the fuzzy rule to enhance the temperature followability. A gray prediction model was added to the feedback loop to give an advanced control effect by predicting the temperature at a future time,thereby weakening the hysteresis of the reactor. The results show that this control method has better response speed and steady-state accuracy than the conventional PID control,and the overshoot is smaller. Finally,it is applied to the ink reaction temperature control,and the control effect is obviously improved.
引文
[1]李晓辉.反应釜温度控制系统的研究[D].太原:太原理工大学,2011.
[2]徐鸿,邓博,蒋东方,等.基于灰色系统的过热器管壁温度预测模型[J].中国机械工程,2017,28(22):2662-2668.
[3]孟红波,王昌明,张爱军.一种基于自适应灰色预测控制的复合控制方法[J].振动与冲击,2016,35(11):123-129.
[4] LU Jianshan,XIE Weidong,ZHOU Hongbo. Vibrationsuppression using fractional-order disturbance observerbased adaptive grey predictive controller[J]. Jve Inter-national Ltd. Journal of Vibroengineering,2014,16(5):2204-2215.
[5] KEUM O L,SOON B L. A comparison of methods forpredicting the fatigue life of gray cast iron at elevatedtemperatures[J]. Fatigue&Fracture of Engineering Ma-terials&Structures,2016,39(4):439-452.
[6]张克非,蒋涛,邵龙,等.基于新型模糊PID控制单元的LD精密温控研究[J].光学精密工程,2017,25(3):648-655.
[7] CHUNG B M,LEE S G,CHO C S. Active Tension Con-trol of High Speed Splitting Machines Using Fuzzy PID[C]//IEEE International Conference on Mecha-tronics. 2005.
[8]彭彦卿,罗键,陈李清.基于PLC的混合型模糊PID在胶温控制系统中的应用[J].厦门大学学报(自然科学版),2008,47(2):191-195.
[9] WANG Y J,DONG X Y,QU Z W. Research on Fuzzy-PID temperature control System for double helix resistor[J]. Applied Mechanics&Materials,2015,738/739:1022-1025.
[10]刘宇,丁其星,郭俊启.基于L-BFGS的自适应模糊互补滤波[J].压电与声光,2018,40(6):955-959.
[11] TANAKA M. A total power control technology on PIDtemperature controllers[J]. Transactions of the Instituteof Electrical Engineers of Japan C,2016(2):112-119.
[12] SONG J L,CHENG W L,XU Z M. Study on PID temper-ature control performance of a novel PTC material withroom temperature Curie point[J]. International Journal ofHeat&Mass Transfer,2016,95(3):1038-1046.
[13]刘思峰,谢乃明.灰色系统理论及其应用[M].北京:科学出版社,2013:91-101.
[14] LU J S,WANG C M,ZHANG A J. Residual GM(1. 1)model-based prediction method for chaotic time series[J]. The Journal of Grey System,2012,24(4):379-388.
[15]秦大同,黄晶莹,刘永刚.电动汽车电池温度加权PID控制[J].交通运输工程学报,2016,16(1):73-79.
[16] CHIDAMBARAM M. Addendum:Set Point Weighting PI/PID Controllers[J]. Chemical Engineering Communica-tion,2002,189(5):710-712.
[17] VISIOLI A. Tuning of PID controllers with fuzzy logic[J]. IEE Proc Control Theory Appl,2001,148(1):1-8.
[18]王春晓,刘海,杜清府.反应釜控制系统的研究与实现[J].化工自动化仪表,2010,37(10):29-32.
[2]徐鸿,邓博,蒋东方,等.基于灰色系统的过热器管壁温度预测模型[J].中国机械工程,2017,28(22):2662-2668.
[3]孟红波,王昌明,张爱军.一种基于自适应灰色预测控制的复合控制方法[J].振动与冲击,2016,35(11):123-129.
[4] LU Jianshan,XIE Weidong,ZHOU Hongbo. Vibrationsuppression using fractional-order disturbance observerbased adaptive grey predictive controller[J]. Jve Inter-national Ltd. Journal of Vibroengineering,2014,16(5):2204-2215.
[5] KEUM O L,SOON B L. A comparison of methods forpredicting the fatigue life of gray cast iron at elevatedtemperatures[J]. Fatigue&Fracture of Engineering Ma-terials&Structures,2016,39(4):439-452.
[6]张克非,蒋涛,邵龙,等.基于新型模糊PID控制单元的LD精密温控研究[J].光学精密工程,2017,25(3):648-655.
[7] CHUNG B M,LEE S G,CHO C S. Active Tension Con-trol of High Speed Splitting Machines Using Fuzzy PID[C]//IEEE International Conference on Mecha-tronics. 2005.
[8]彭彦卿,罗键,陈李清.基于PLC的混合型模糊PID在胶温控制系统中的应用[J].厦门大学学报(自然科学版),2008,47(2):191-195.
[9] WANG Y J,DONG X Y,QU Z W. Research on Fuzzy-PID temperature control System for double helix resistor[J]. Applied Mechanics&Materials,2015,738/739:1022-1025.
[10]刘宇,丁其星,郭俊启.基于L-BFGS的自适应模糊互补滤波[J].压电与声光,2018,40(6):955-959.
[11] TANAKA M. A total power control technology on PIDtemperature controllers[J]. Transactions of the Instituteof Electrical Engineers of Japan C,2016(2):112-119.
[12] SONG J L,CHENG W L,XU Z M. Study on PID temper-ature control performance of a novel PTC material withroom temperature Curie point[J]. International Journal ofHeat&Mass Transfer,2016,95(3):1038-1046.
[13]刘思峰,谢乃明.灰色系统理论及其应用[M].北京:科学出版社,2013:91-101.
[14] LU J S,WANG C M,ZHANG A J. Residual GM(1. 1)model-based prediction method for chaotic time series[J]. The Journal of Grey System,2012,24(4):379-388.
[15]秦大同,黄晶莹,刘永刚.电动汽车电池温度加权PID控制[J].交通运输工程学报,2016,16(1):73-79.
[16] CHIDAMBARAM M. Addendum:Set Point Weighting PI/PID Controllers[J]. Chemical Engineering Communica-tion,2002,189(5):710-712.
[17] VISIOLI A. Tuning of PID controllers with fuzzy logic[J]. IEE Proc Control Theory Appl,2001,148(1):1-8.
[18]王春晓,刘海,杜清府.反应釜控制系统的研究与实现[J].化工自动化仪表,2010,37(10):29-32.