一类网络控制系统可靠性研究
|
摘要
随着网络技术和控制技术的迅猛发展和广泛应用,网络化控制系统的理论研究和应用成为当前控制领域中的热点之一,也是未来工业控制系统的发展趋势。由于控制系统引入通信网络之后,成为网络化、分布化的新型模式,因此,如何描述网络控制系统的可靠性,并预测其变化规律,是网络控制系统研究中急需解决的问题之一,也是本论文研究的主要内容。
首先,论文介绍了网络控制系统的基本概念及其性能指标,给出了网络控制系统可靠性的概念,并选取了可靠性指标。同时,介绍了设计网络控制系统仿真平台的两种方法；然后,在一定的假设条件下,建立了网络控制系统的Markov可靠性模型,运用Markov状态转移方法,通过Laplace变换和Laplace反变换求出可靠性的大小。其次,针对工业控制系统中传感器失效率时变的特点,设计了传感器失效率时变的网络控制系统可靠性模型,在失效率为正弦变化和指数变化的假设下求得了可靠性的大小；再其次,针对分布式传感器网络中故障点多、可靠性参数估计困难的特点,提出了一种基于模糊神经网络的Markov可靠性模型,验证了模型的正确性及其优点；最后,介绍了基于CC-LINK现场总线技术的彩报印刷墨色预置分布式控制系统,并将Markov可靠性模型和模糊神经网络Markov可靠性模型应用到该系统的可靠性预测中。
With the rapid development and wide use of internet and control technology, theoretic study and application of networked control systems has become one of the hot points of control community, and it will be the trend of industrial control in the future. Owing to the introduction of internet to control system, it has become a internalized and distributed new model. So how to describe the reliability of networked control system and anticipate its regular pattern has become one of the most urging problems in NCS, and it is also the main content in this thesis.
At first, the basic concept and properties targets of Networked Control System are first introduced, and give the concept of NCS and choose its properties targets. In the meanwhile, introduce two main methods of how to simulate networked control system; then give the Markov reliability model. Using Laplace transferring and Laplace anti-transferring methods to calculate its reliability based on some assumed conditions; after that, aiming at the characteristic of time-varying failure rate of sensors in real control, assume that the failure rates follow sine varying and exponential varying and calculate its reliability; and then aiming at the characteristic of the variety of faults and difficult to estimate its reliability parameter, the Markov reliability model based on fuzzy neural network is presented. Simulation result shows that the neural model is correct. At last, introduce the whole design method of ink pre-configuration distributed control system, a control method based on CC-LINK is given. Then the Markov reliability model and FNN Markov reliability model are used in the system.
首先,论文介绍了网络控制系统的基本概念及其性能指标,给出了网络控制系统可靠性的概念,并选取了可靠性指标。同时,介绍了设计网络控制系统仿真平台的两种方法；然后,在一定的假设条件下,建立了网络控制系统的Markov可靠性模型,运用Markov状态转移方法,通过Laplace变换和Laplace反变换求出可靠性的大小。其次,针对工业控制系统中传感器失效率时变的特点,设计了传感器失效率时变的网络控制系统可靠性模型,在失效率为正弦变化和指数变化的假设下求得了可靠性的大小；再其次,针对分布式传感器网络中故障点多、可靠性参数估计困难的特点,提出了一种基于模糊神经网络的Markov可靠性模型,验证了模型的正确性及其优点；最后,介绍了基于CC-LINK现场总线技术的彩报印刷墨色预置分布式控制系统,并将Markov可靠性模型和模糊神经网络Markov可靠性模型应用到该系统的可靠性预测中。
With the rapid development and wide use of internet and control technology, theoretic study and application of networked control systems has become one of the hot points of control community, and it will be the trend of industrial control in the future. Owing to the introduction of internet to control system, it has become a internalized and distributed new model. So how to describe the reliability of networked control system and anticipate its regular pattern has become one of the most urging problems in NCS, and it is also the main content in this thesis.
At first, the basic concept and properties targets of Networked Control System are first introduced, and give the concept of NCS and choose its properties targets. In the meanwhile, introduce two main methods of how to simulate networked control system; then give the Markov reliability model. Using Laplace transferring and Laplace anti-transferring methods to calculate its reliability based on some assumed conditions; after that, aiming at the characteristic of time-varying failure rate of sensors in real control, assume that the failure rates follow sine varying and exponential varying and calculate its reliability; and then aiming at the characteristic of the variety of faults and difficult to estimate its reliability parameter, the Markov reliability model based on fuzzy neural network is presented. Simulation result shows that the neural model is correct. At last, introduce the whole design method of ink pre-configuration distributed control system, a control method based on CC-LINK is given. Then the Markov reliability model and FNN Markov reliability model are used in the system.
引文
[1]郑文波.控制网络技术[M].清华大学出版社.2001
[2]G C Walsh, H Ye, L Bushnel. Stability Analysis of Networked Control System[C]. San Diego. USA:Proceedings of American Control Conference,1999:2876-2880
[3]李人厚.智能控制理论方法[M].西安电子科技大学出版社.1999
[4]孙玉秋,印刷过程建模与系统辨识[J].北京印刷学院学报,1999.3
[5]Y H Kim, W H Kwon, H S Park. Stability and a Scheduling Method for Network-based Control Systems[C]. Taipei Taiwan:Proceedings of the 22nd Annual Conference of the IEEE Industrial Electronics Society,1996:934-939
[6]Jing Wu, Tongwen Chen. Design of Networked Control Systems With Packet Dropouts[J]. IEEE Transactions on Automatic Control,2007,52(7):1314-1319
[7]Nilsson. Real-time control systems with delays[D]. Lund, Sweden:Department of Automatic Control Lund Institute of Technology,1998
[8]Wei Zhang Michael Branicky, Stephen Phillips. Stability of networked control systems[J]. IEEE Control Systems,2001,21 (1):85-99
[9]Fengli Lian. Analysis, Design Modeling and Control of Networked Control Systems[D].University of Michigan,2001
[10]W Zhang. Stabability Analysis of Networked Control Systems[D]. Case Western Reserve University,2001.
[11]邱占芝,张庆灵.一类多输入多输出网络控制系统的稳定性分析[J].控制与决策,2005,20(5)：525-528,544.
[12]于之训,陈辉堂,蒋平.具有传输延迟的网络控制系统中状态观测器的设计[J].信息与控制,2000,15(3)：125-130.
[13]SHu,Q Zhu. Stochastic Optimal Control and Analysis of Stability of Networked Control Systems with Long Delay[J]. Automatica,2003, (39):1877-1884
[14]H Lin,G S Zhai Antsaklis. Robust stability and disturbance attenuation analysis of a class of networked control systems[C].Maui Hawaii USA:Proceedings of the 42nd IEEE Conference on Decision and Control 2003:1182-1187
[15]周祖德.基于网络环境的智能控制[M].北京：国防工业出版社,2004
[16]Z Li,H J Fang. A novel controller design and evaluation for networked control systems with time-variant delay [J]. Journal of the Franklin Institute,2006,343 (2):161-167
[17]费敏锐,李力雄.基于网络学习的控制系统[C].香港：中国智能自动化大会论文集,2003：180-185,168
[18]王常力,廖道文.集散控制系统的设计与应用[M].北京：清华大学出社,1993
[19]楼顺天,胡昌华,张伟.基于MATLAB的系统分析与设计——模糊系统[M].西安电子科技大学出版社,2003
[20]李洪兴,汪培庄.模糊数学[M].国防工业出版社.1993
[21]许力.智能控制与智能系统[M].北京：机械工业出版社.2007
[22]魏利胜,费敏锐.分布式网络控制系统研究进展[J].工业仪表与自动化装置,2009(2)：16-21
[23]Xin Yao. Evolving Artificial Networks. Proceeding of the IEEE,1999,87 (9):1423-1447
[24]王冬青.带误差补偿的GPC对网络控制系统时延的解决[J].中国工程科学,005,7[8]：60-64
[25]牛志平,等.网络控制系统的仿真研究[J].计算机应用,2008(28)：232-235
[26]张芳,等.网络控制系统仿真平台的研究[J].现代电子技术,2007(9)：90-92
[27]钱美,等.基于Matlab的网络控制系统仿真[J].微计算机信息,2007,23(4)：117-119
[28]郭永基.可靠性工程原理[M].北京：清华大学出版社,2002
[29]魏利胜,费敏锐.基于马尔可夫模型的NCS可靠性分析[J].工业仪表与自动化装置,2007,5：6-13
[30]周应兵.基于马尔可夫过程的控制系统可靠性分析[J].山东交通学院学报,2005,13(1)：7-10
[31]黎善斌,孙优贤,等.网络控制系统的研究现状与展望[J].信息与控制,2003,32(3)
[32]王子君,等.网络控制系统研究综述[J].自动化仪表,2005,26(10)
[33]项林英,等.网络控制系统的控制方法研究[J].兰州理工大学学报,2005,31(6)：93-99
[33]马宝甫,等.微机应用系统可靠性设计理论与实践[M].北京：电子工业出版社,1999
[34]焦正,等.分布式传感器网络研究进展[J].传感器世界,2004(10)：6-10
[35]刘美俊.基于混合学习算法的模糊神经网络控制系统[J].厦门理工学院学报, 2009,17(1)：36-41
[36]严鸿瑞,马礼举.基于模糊神经网络智能预测模型的设计与实现[J].现代电子技术,2008(2)：84-89
[37]王雪苗.模糊神经网络优化及应用研究[D].大连理工大学.2006
[38]孙海蓉.模糊神经网络的研究及其应用[D].华北电力大学.2006
[39]贾惠芹,刘君华.基于BP神经网络的分布式传感器网络的可靠性分析[J].铁道学报,2002,24(5)：80-83
[40]张国鹏,王晓凯,邓娜.基于Markov过程的网络控制系统可靠性研究,软件导刊,2010,9,(1)：116-118
[41]李志勇.彩报印刷墨色预置分布式控制系统的设计与研究[D].山西大学.2008
[42]李春洋,等.基于马尔科夫过程的k／n系统共因失效分析[J].系统工程与电子技术,2009,31(11)：2790-2792
[43]徐勇,等.系统可靠性分配的神经网络模型[J].系统工程与电子技术,2001,23,(1)：90-92
[44]王昕.神经网络在系统可靠性分配中的应用[J].长春工程学院学报,2003,4,(1)：66-67
[45]王蓓.优化BP神经网络的可靠性预测模型[J].计算机技术与发展,2007,17,(9)：102-105
[46]Mahmoud A, Manzoul M S. Neural network for the reliability analysis of simplex systems[J]. Microelectron. Reliab,1990,30(4):795-800
[2]G C Walsh, H Ye, L Bushnel. Stability Analysis of Networked Control System[C]. San Diego. USA:Proceedings of American Control Conference,1999:2876-2880
[3]李人厚.智能控制理论方法[M].西安电子科技大学出版社.1999
[4]孙玉秋,印刷过程建模与系统辨识[J].北京印刷学院学报,1999.3
[5]Y H Kim, W H Kwon, H S Park. Stability and a Scheduling Method for Network-based Control Systems[C]. Taipei Taiwan:Proceedings of the 22nd Annual Conference of the IEEE Industrial Electronics Society,1996:934-939
[6]Jing Wu, Tongwen Chen. Design of Networked Control Systems With Packet Dropouts[J]. IEEE Transactions on Automatic Control,2007,52(7):1314-1319
[7]Nilsson. Real-time control systems with delays[D]. Lund, Sweden:Department of Automatic Control Lund Institute of Technology,1998
[8]Wei Zhang Michael Branicky, Stephen Phillips. Stability of networked control systems[J]. IEEE Control Systems,2001,21 (1):85-99
[9]Fengli Lian. Analysis, Design Modeling and Control of Networked Control Systems[D].University of Michigan,2001
[10]W Zhang. Stabability Analysis of Networked Control Systems[D]. Case Western Reserve University,2001.
[11]邱占芝,张庆灵.一类多输入多输出网络控制系统的稳定性分析[J].控制与决策,2005,20(5)：525-528,544.
[12]于之训,陈辉堂,蒋平.具有传输延迟的网络控制系统中状态观测器的设计[J].信息与控制,2000,15(3)：125-130.
[13]SHu,Q Zhu. Stochastic Optimal Control and Analysis of Stability of Networked Control Systems with Long Delay[J]. Automatica,2003, (39):1877-1884
[14]H Lin,G S Zhai Antsaklis. Robust stability and disturbance attenuation analysis of a class of networked control systems[C].Maui Hawaii USA:Proceedings of the 42nd IEEE Conference on Decision and Control 2003:1182-1187
[15]周祖德.基于网络环境的智能控制[M].北京：国防工业出版社,2004
[16]Z Li,H J Fang. A novel controller design and evaluation for networked control systems with time-variant delay [J]. Journal of the Franklin Institute,2006,343 (2):161-167
[17]费敏锐,李力雄.基于网络学习的控制系统[C].香港：中国智能自动化大会论文集,2003：180-185,168
[18]王常力,廖道文.集散控制系统的设计与应用[M].北京：清华大学出社,1993
[19]楼顺天,胡昌华,张伟.基于MATLAB的系统分析与设计——模糊系统[M].西安电子科技大学出版社,2003
[20]李洪兴,汪培庄.模糊数学[M].国防工业出版社.1993
[21]许力.智能控制与智能系统[M].北京：机械工业出版社.2007
[22]魏利胜,费敏锐.分布式网络控制系统研究进展[J].工业仪表与自动化装置,2009(2)：16-21
[23]Xin Yao. Evolving Artificial Networks. Proceeding of the IEEE,1999,87 (9):1423-1447
[24]王冬青.带误差补偿的GPC对网络控制系统时延的解决[J].中国工程科学,005,7[8]：60-64
[25]牛志平,等.网络控制系统的仿真研究[J].计算机应用,2008(28)：232-235
[26]张芳,等.网络控制系统仿真平台的研究[J].现代电子技术,2007(9)：90-92
[27]钱美,等.基于Matlab的网络控制系统仿真[J].微计算机信息,2007,23(4)：117-119
[28]郭永基.可靠性工程原理[M].北京：清华大学出版社,2002
[29]魏利胜,费敏锐.基于马尔可夫模型的NCS可靠性分析[J].工业仪表与自动化装置,2007,5：6-13
[30]周应兵.基于马尔可夫过程的控制系统可靠性分析[J].山东交通学院学报,2005,13(1)：7-10
[31]黎善斌,孙优贤,等.网络控制系统的研究现状与展望[J].信息与控制,2003,32(3)
[32]王子君,等.网络控制系统研究综述[J].自动化仪表,2005,26(10)
[33]项林英,等.网络控制系统的控制方法研究[J].兰州理工大学学报,2005,31(6)：93-99
[33]马宝甫,等.微机应用系统可靠性设计理论与实践[M].北京：电子工业出版社,1999
[34]焦正,等.分布式传感器网络研究进展[J].传感器世界,2004(10)：6-10
[35]刘美俊.基于混合学习算法的模糊神经网络控制系统[J].厦门理工学院学报, 2009,17(1)：36-41
[36]严鸿瑞,马礼举.基于模糊神经网络智能预测模型的设计与实现[J].现代电子技术,2008(2)：84-89
[37]王雪苗.模糊神经网络优化及应用研究[D].大连理工大学.2006
[38]孙海蓉.模糊神经网络的研究及其应用[D].华北电力大学.2006
[39]贾惠芹,刘君华.基于BP神经网络的分布式传感器网络的可靠性分析[J].铁道学报,2002,24(5)：80-83
[40]张国鹏,王晓凯,邓娜.基于Markov过程的网络控制系统可靠性研究,软件导刊,2010,9,(1)：116-118
[41]李志勇.彩报印刷墨色预置分布式控制系统的设计与研究[D].山西大学.2008
[42]李春洋,等.基于马尔科夫过程的k／n系统共因失效分析[J].系统工程与电子技术,2009,31(11)：2790-2792
[43]徐勇,等.系统可靠性分配的神经网络模型[J].系统工程与电子技术,2001,23,(1)：90-92
[44]王昕.神经网络在系统可靠性分配中的应用[J].长春工程学院学报,2003,4,(1)：66-67
[45]王蓓.优化BP神经网络的可靠性预测模型[J].计算机技术与发展,2007,17,(9)：102-105
[46]Mahmoud A, Manzoul M S. Neural network for the reliability analysis of simplex systems[J]. Microelectron. Reliab,1990,30(4):795-800