船舶柴油机变论域模糊PID转速控制研究
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摘要
由于计算机技术、总线技术、控制技术、网络技术等飞速发展,计算机在船舱自动化中的应用变得越来越广泛,尤其是在信息交换、实时控制和控制算法仿真领域的应用更为突出。随着我国船舶信息技术的飞速发展,基于现场总线技术和组态软件的网络构架已经能够实现船舶航行过程的一体化和自动化,它能代替轮机员正确地实现对机舱中的主辅机等设备和各个子系统的巡视管理、监视、和控制。
本文在船舱自动化网络系统建立的基础上,对船舶柴油机系统的数学建模和控制算法进行了深入细致的研究。针对船舶柴油机系统的特点,以变论域模糊控制和PID控制相结合设计了变论域模糊PID控制器,并基于船舶自动化网络,搭建了柴油机半实物网络仿真平台及上位机监控系统,实现了系统的实际运行。
首先,本文以MATLAB/SIMULINK软件为平台,建立了柴油机的平均值模型,然后针对该被控对象,进行了控制算法的设计。根据传统PID控制在船用柴油机转速控制上的不足,设计了基于变论域的模糊PID控制器。该控制器不仅实现了PID参数的在线自整定,还较好的提高了船用柴油机转速控制器的控制性能。仿真结果表明,变论域模糊PID控制器在系统超调量、响应时间上都有明显的改善。最后,在研华工控机的MATLAB/RTW环境下建立了柴油机实时仿真平台,利用该平台来替代真实的柴油机对象。通过接入DSP控制器、ANYCAN节点和整个船舱以太网-CAN网络构建了柴油机半实物网络仿真系统,上位机利用iFIX组态软件实现了柴油机系统运行状况的实时监控。
本文的研究工作为后期的实船试验打下了基础,更为重要的是提出了一种实现船舶柴油机转速控制的较为先进的控制策略,为后继研究者提供了理论和技术支持,缩短了开发周期,对船舶柴油机电控技术的发展必将起到积极的推动作用。
As the rapid development of computer technology, bus technology, control technology, and network technology, computer has been largely applied in cabin automation systems, especially in the exchange of information, real-time control, and control algorithm areas. With rapid development of Chinese shipbuilding industry, the framework which is based on field bus and configuration software has already been applied in navigation. This system can replace the engineer to act as patrol manager, monitor, and controller.
The mathematical model of marine diesel as well as speed control algorithms have been thoroughly researched in this paper. With the combination of PID control and fuzzy logic control, the variable universe fuzzy PID controller has been proposed. Besides, a semi-physical simulation platform as well as a monitoring and control system have also been built, which has already been realized in the simulation system.
At first, the average model of marine diesel has been built in MATLAB/SIMULINK. And then, according to such model, some studies on the control algorithms have been conducted. A variable universe fuzzy controller has been designed according to the short points of conventional PID controller as well as the fuzzy logic controller. This variable universe fuzzy PID can not only self-regulate the parameters but also ameliorate the control performances. Comparing with the simulation results of conventional PID control, this variable universe fuzzy PID control has a large improvement in overshot as well as response time. At last, the MATLAB/RTW real-time system has been built in Advantech IPC, which is applied to replace the real marine diesel system. And the whole semi-physical simulation platform is composed of this RTW system, DSP controller, ANYCAN nodes, as well as the whole Internet-CAN network. In the host computer, iFIX configuration software is adopted to design the whole monitor and control interface.
The research of this paper is considered as the basis for the test of practical cabin system. And more important, a comparative new algorithm for marine diesel speed control is proposed. This research for marine diesel speed controller would no doubt provide theoretical as well as technological support for the later studies, which can shorten the development cycle, and play a positive role for the diesel electronic control technology.
本文在船舱自动化网络系统建立的基础上,对船舶柴油机系统的数学建模和控制算法进行了深入细致的研究。针对船舶柴油机系统的特点,以变论域模糊控制和PID控制相结合设计了变论域模糊PID控制器,并基于船舶自动化网络,搭建了柴油机半实物网络仿真平台及上位机监控系统,实现了系统的实际运行。
首先,本文以MATLAB/SIMULINK软件为平台,建立了柴油机的平均值模型,然后针对该被控对象,进行了控制算法的设计。根据传统PID控制在船用柴油机转速控制上的不足,设计了基于变论域的模糊PID控制器。该控制器不仅实现了PID参数的在线自整定,还较好的提高了船用柴油机转速控制器的控制性能。仿真结果表明,变论域模糊PID控制器在系统超调量、响应时间上都有明显的改善。最后,在研华工控机的MATLAB/RTW环境下建立了柴油机实时仿真平台,利用该平台来替代真实的柴油机对象。通过接入DSP控制器、ANYCAN节点和整个船舱以太网-CAN网络构建了柴油机半实物网络仿真系统,上位机利用iFIX组态软件实现了柴油机系统运行状况的实时监控。
本文的研究工作为后期的实船试验打下了基础,更为重要的是提出了一种实现船舶柴油机转速控制的较为先进的控制策略,为后继研究者提供了理论和技术支持,缩短了开发周期,对船舶柴油机电控技术的发展必将起到积极的推动作用。
As the rapid development of computer technology, bus technology, control technology, and network technology, computer has been largely applied in cabin automation systems, especially in the exchange of information, real-time control, and control algorithm areas. With rapid development of Chinese shipbuilding industry, the framework which is based on field bus and configuration software has already been applied in navigation. This system can replace the engineer to act as patrol manager, monitor, and controller.
The mathematical model of marine diesel as well as speed control algorithms have been thoroughly researched in this paper. With the combination of PID control and fuzzy logic control, the variable universe fuzzy PID controller has been proposed. Besides, a semi-physical simulation platform as well as a monitoring and control system have also been built, which has already been realized in the simulation system.
At first, the average model of marine diesel has been built in MATLAB/SIMULINK. And then, according to such model, some studies on the control algorithms have been conducted. A variable universe fuzzy controller has been designed according to the short points of conventional PID controller as well as the fuzzy logic controller. This variable universe fuzzy PID can not only self-regulate the parameters but also ameliorate the control performances. Comparing with the simulation results of conventional PID control, this variable universe fuzzy PID control has a large improvement in overshot as well as response time. At last, the MATLAB/RTW real-time system has been built in Advantech IPC, which is applied to replace the real marine diesel system. And the whole semi-physical simulation platform is composed of this RTW system, DSP controller, ANYCAN nodes, as well as the whole Internet-CAN network. In the host computer, iFIX configuration software is adopted to design the whole monitor and control interface.
The research of this paper is considered as the basis for the test of practical cabin system. And more important, a comparative new algorithm for marine diesel speed control is proposed. This research for marine diesel speed controller would no doubt provide theoretical as well as technological support for the later studies, which can shorten the development cycle, and play a positive role for the diesel electronic control technology.
引文
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[2]喻方平,微型计算机在船舶中的应用[M].电子工业出版社,1997.
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[5] G. Schickhuber, 0. McCarthy“Distributed fieldbus and control network systems”[J]. COMPUTING and CONTROL ENGINEERING JOURNAL, Feb 1997.
[6] FARSIM,RATCLIFFK,BARBOSA,etal. Overview of Control area Network[J].Computing and Control Engineering Journal,1999,10(3):113-120.
[7]唐开元,欧阳光耀.高等内燃机学[M].北京:国防工业出版社,2008.
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[9]张元涛,王凤霞,石为人.大型低速二冲程船用柴油机建模及仿真[J].船舶工程,2009,31(3):11-14.
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[13]许道延,丁贤华.告诉柴油机概念设计与实践[M].北京:机械工业出版社,2004.
[14]王海燕,胡以怀.船用柴油机的分缸平均值模型[J].哈尔滨工程大学报, 2009,30(7):741-746.
[15]王海燕,张均东,任光.大型船用柴油机建模与动态仿真[J].系统仿真学报,2006,18(9):2538-2675.
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[17] Han, Zhiping. Diesel engine cold start combustion instability and control strategy[D].Detroit:Wayne State University,2000.
[18]帅英梅,高世伦.涡轮增压柴油机的平均值模型及仿真[J].柴油机设计与制造,2004,2:19-23.
[19] Garcia, Sergio Leonardo. Modeling and analysis of dynamic behavior of hybrid wind-diesel power plants[D].Toronto:University of Toronto,2007.
[20] Jeffries, William Q. Analysis and modeling of wind/diesel systems withoutstorage[D].Massachusetts:University of Massachusetts Amherst,1994.
[21] Wang Hong-qiao, Yang Ming-gao, Li Jin. A type of Real-time Simulation System for Electronic Diesel Engine Controller[J]. Transaction of CSICE, 2002,20(1):37-40.
[22]孔峰,宋希庚,张育华,宋雪桦,曾洁.增压中冷电控单体泵柴油机的平均值模型[J].内燃机工程,2006, 27(5):20-23.
[23]朱晶.基于模糊PID的三容水箱液位控制系统应用研究[D].大连:大连理工大学, 2008.
[24] Xu, Jingwei. Fuzzy PID control through optimization: A new method for PID control[D].Milwaukee:Marquette University,2006.
[25] Misir, Daywayshwar D. New design, stability analysis and applications of auto-tuned fuzzy PID controllers[D].Houston:University of Houston,1996.
[26] Dong, Puxuan. Design, analysis and real-time realization of artificial neural network for control and classification[D].North Carolina:North Carolina State University,2006.
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[31] Jowers, Leonard J. Fuzzy systems simulation: Models, foundations, and systems development[D].Birmingham: The University of Alabama at Birmingham,2007.
[32] JunYoneyama. Robust H∞control analysis and synthesis for Takagi–Sugeno general uncertain fuzzy systems [J]. Fuzzy Sets and Systems, 2006 (157): 2205-2223.
[33] Antonio Sala, Thierry Marie Guerra, Robert Babu ka. Perspectives of fuzzy systems and control[J]. Fuzzy Sets and Systems, 2005 (156): 432-444
[34]钟飞,钟毓宁. Mamdani与Sugeno型模糊推理的应用研究[J].湖北工业大学学报, 2005,20 (2): 28-30.
[35]王立新,王迎军.模糊系统与模糊控制[M].北京:清华大学出版社,2003.
[36]刘大鹏.基于可变论域模糊控制的柴油机调速器研究[D].哈尔滨:哈尔滨理工大学, 2009.
[37]潘永平,王钦若.变论域自适应模糊PID控制器设计[J].电气自动化,2007, 29 (3): 9-12.
[38]李洪兴.变论域自适应模糊控制器.中国科学,E辑,1999,29(l):32-42.
[39]彭家寅,李洪兴.基于逐点优化模糊推理的模糊控制器及插值机理[J].系统科学与数学,2005,25(3):311-322.
[40]王艺.变论域自适应模糊控制器的研究[D].重庆:西南师范大学, 2004:14-18.
[41] Liu, Zeng Lian. Control and simulation investigation of wing rock phenomenon[D].Montreal:Concordia University, 2005.
[42]李良峰.变论域模糊控制算法研究[D].成都:电子科技大学, 2008, 30-41.
[43]王璐.时滞系统变论域模糊自调整内模控制[D].北京:北京化工大学, 2008.
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[2]喻方平,微型计算机在船舶中的应用[M].电子工业出版社,1997.
[3]牛宝来,船舶自动控制系统,大连海运学院出版社[M].1990.
[4]武晓云.船舶机舱自动化CAN现场总线监控系统体系结构及功能描述[J].中国造船, 2001, 42(1):69-74.
[5] G. Schickhuber, 0. McCarthy“Distributed fieldbus and control network systems”[J]. COMPUTING and CONTROL ENGINEERING JOURNAL, Feb 1997.
[6] FARSIM,RATCLIFFK,BARBOSA,etal. Overview of Control area Network[J].Computing and Control Engineering Journal,1999,10(3):113-120.
[7]唐开元,欧阳光耀.高等内燃机学[M].北京:国防工业出版社,2008.
[8]王斌斌,船舶柴油机转速控制仿真研究[D].大连:大连海事大学,2009.
[9]张元涛,王凤霞,石为人.大型低速二冲程船用柴油机建模及仿真[J].船舶工程,2009,31(3):11-14.
[10]林楠,船舶柴油机建模及转速控制仿真研究[D].大连:大连海事大学,2008.
[11]王尚勇,杨青.柴油机电子控制技术[M].北京:机械工业出版社,2005.
[12]汤明,船舶柴油机控制模型研究[J].工程技术,2009,33:58-59.
[13]许道延,丁贤华.告诉柴油机概念设计与实践[M].北京:机械工业出版社,2004.
[14]王海燕,胡以怀.船用柴油机的分缸平均值模型[J].哈尔滨工程大学报, 2009,30(7):741-746.
[15]王海燕,张均东,任光.大型船用柴油机建模与动态仿真[J].系统仿真学报,2006,18(9):2538-2675.
[16] Brahma, Avra. Methodologies for modeling and feedback control of the nitrogen oxide-BSFC trade-off in high-speed, common-rail, direct-injection diesel engines[D].Ohio:The Ohio State University,2005.
[17] Han, Zhiping. Diesel engine cold start combustion instability and control strategy[D].Detroit:Wayne State University,2000.
[18]帅英梅,高世伦.涡轮增压柴油机的平均值模型及仿真[J].柴油机设计与制造,2004,2:19-23.
[19] Garcia, Sergio Leonardo. Modeling and analysis of dynamic behavior of hybrid wind-diesel power plants[D].Toronto:University of Toronto,2007.
[20] Jeffries, William Q. Analysis and modeling of wind/diesel systems withoutstorage[D].Massachusetts:University of Massachusetts Amherst,1994.
[21] Wang Hong-qiao, Yang Ming-gao, Li Jin. A type of Real-time Simulation System for Electronic Diesel Engine Controller[J]. Transaction of CSICE, 2002,20(1):37-40.
[22]孔峰,宋希庚,张育华,宋雪桦,曾洁.增压中冷电控单体泵柴油机的平均值模型[J].内燃机工程,2006, 27(5):20-23.
[23]朱晶.基于模糊PID的三容水箱液位控制系统应用研究[D].大连:大连理工大学, 2008.
[24] Xu, Jingwei. Fuzzy PID control through optimization: A new method for PID control[D].Milwaukee:Marquette University,2006.
[25] Misir, Daywayshwar D. New design, stability analysis and applications of auto-tuned fuzzy PID controllers[D].Houston:University of Houston,1996.
[26] Dong, Puxuan. Design, analysis and real-time realization of artificial neural network for control and classification[D].North Carolina:North Carolina State University,2006.
[27]韩俊峰,李玉惠.模糊控制技术[M].重庆:重庆大学出版社,2003.
[28] Green, Anthony. Intelligent tracking control of fixed-base and free-flying flexible space robots[D].Ottawa: Carleton University,2006.
[29]柯熙政,邓方林.模糊控制及其MATLAB应用[M].西安:西安交通大学出版社,2002.
[30] Xu, Chengying. Intelligent multivariable control system[D] . West Lafayette: Purdue University,2006.
[31] Jowers, Leonard J. Fuzzy systems simulation: Models, foundations, and systems development[D].Birmingham: The University of Alabama at Birmingham,2007.
[32] JunYoneyama. Robust H∞control analysis and synthesis for Takagi–Sugeno general uncertain fuzzy systems [J]. Fuzzy Sets and Systems, 2006 (157): 2205-2223.
[33] Antonio Sala, Thierry Marie Guerra, Robert Babu ka. Perspectives of fuzzy systems and control[J]. Fuzzy Sets and Systems, 2005 (156): 432-444
[34]钟飞,钟毓宁. Mamdani与Sugeno型模糊推理的应用研究[J].湖北工业大学学报, 2005,20 (2): 28-30.
[35]王立新,王迎军.模糊系统与模糊控制[M].北京:清华大学出版社,2003.
[36]刘大鹏.基于可变论域模糊控制的柴油机调速器研究[D].哈尔滨:哈尔滨理工大学, 2009.
[37]潘永平,王钦若.变论域自适应模糊PID控制器设计[J].电气自动化,2007, 29 (3): 9-12.
[38]李洪兴.变论域自适应模糊控制器.中国科学,E辑,1999,29(l):32-42.
[39]彭家寅,李洪兴.基于逐点优化模糊推理的模糊控制器及插值机理[J].系统科学与数学,2005,25(3):311-322.
[40]王艺.变论域自适应模糊控制器的研究[D].重庆:西南师范大学, 2004:14-18.
[41] Liu, Zeng Lian. Control and simulation investigation of wing rock phenomenon[D].Montreal:Concordia University, 2005.
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