模糊控制在电梯群控系统中的应用研究
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摘要
随着当今大型建筑物的不断发展,其内部的交通状况越来越复杂,独立的电梯已经不能胜任大楼内的交通任务。于是人们开始研究电梯群控技术,这种技术将几部电梯组成电梯群进行统一调度。目前,国内外对电梯群控系统的研究越来越广泛。
电梯群控系统中存在着大量的非线性、不确定性等,在其发展初期一般的控制方法还能适用。但现今,电梯的应用不断增多,人们对电梯的服务提出的要求也越来越高,传统的控制方法已经不能起到很好的效果。于是,人们将近些年发展很快的人工智能技术应用到电梯群控系统中。如模糊控制,它能够解决那些对被控对象无法建立精确模型甚至无法建模的控制问题。另外,模糊控制依赖于知识库,非常接近人的思维,能使问题得到更有效的控制。
本文在分析电梯群控发展过程的基础上讨论了人工智能技术在电梯群控系统中的应用前景,并结合电梯群控系统的一些特点指出了其中影响系统整体性能的一些因素,这些因素都是在系统进行调度时重点优化的目标。为了研究和建模的需要,本文对一般大楼内的交通客流情况进行了分析并将其分成了几种模式,然后讨论了利用模糊逻辑对交通模式进行辨识的过程,在此基础上探讨了模糊控制在群控调度中的应用。最后进行的仿真表明,将模糊控制应用在群控系统中能改善系统的性能,提高系统的服务质量。
With the development of the large-scale construction nowadays, the traffic in a large building has become more and more complex and the single elevator has been not competent for the transport missions. So, the research of elevator group control is been started. This technique combines several single elevators into elevator group and dispatches them all together. The research of elevator group control system has been widely carried out at home and abroad at present.
A large number of nonlinearities and uncertainties exist in the elevator group control system. The traditional control methods can be used at the early stage of its development. With more and more applications of elevator and the higher and higher requirement of people when they take lift, the traditional control methods have been not able to achieve the goal very well. So, the technique of artificial intelligence which is developing at a high speed in recent years is applied to the elevator group control system. For example, the technique of fuzzy control can solve many problems in which we can’t build the model or the accurate model of the controlled objects. Otherwise,the technique of fuzzy control depends on repository and it is close to the thoughts of human .We can deal with problems more efficaciously by this technique.
Based on the analysis of the development of the elevator group control system, this thesis has discussed the prospect of the application of artificial intelligence to the elevator group control system. According to some characteristics of the elevator group control system, this thesis points out the factors that influence the population performance of the system. These factors are the mainly optimized factors in the course of group control. For the need of research and modeling, this thesis analyses traffic circumstance in a building and divides it into several kinds of pattern and mainly discusses the application of fuzzy control to the traffic pattern recognition. Base on this, this thesis discusses t the application of the fuzzy control to the group control and dispatch .The results of simulation indicate that the application of fuzzy control to elevator group control system can improve the whole performance and the quality of its services evidently.
电梯群控系统中存在着大量的非线性、不确定性等,在其发展初期一般的控制方法还能适用。但现今,电梯的应用不断增多,人们对电梯的服务提出的要求也越来越高,传统的控制方法已经不能起到很好的效果。于是,人们将近些年发展很快的人工智能技术应用到电梯群控系统中。如模糊控制,它能够解决那些对被控对象无法建立精确模型甚至无法建模的控制问题。另外,模糊控制依赖于知识库,非常接近人的思维,能使问题得到更有效的控制。
本文在分析电梯群控发展过程的基础上讨论了人工智能技术在电梯群控系统中的应用前景,并结合电梯群控系统的一些特点指出了其中影响系统整体性能的一些因素,这些因素都是在系统进行调度时重点优化的目标。为了研究和建模的需要,本文对一般大楼内的交通客流情况进行了分析并将其分成了几种模式,然后讨论了利用模糊逻辑对交通模式进行辨识的过程,在此基础上探讨了模糊控制在群控调度中的应用。最后进行的仿真表明,将模糊控制应用在群控系统中能改善系统的性能,提高系统的服务质量。
With the development of the large-scale construction nowadays, the traffic in a large building has become more and more complex and the single elevator has been not competent for the transport missions. So, the research of elevator group control is been started. This technique combines several single elevators into elevator group and dispatches them all together. The research of elevator group control system has been widely carried out at home and abroad at present.
A large number of nonlinearities and uncertainties exist in the elevator group control system. The traditional control methods can be used at the early stage of its development. With more and more applications of elevator and the higher and higher requirement of people when they take lift, the traditional control methods have been not able to achieve the goal very well. So, the technique of artificial intelligence which is developing at a high speed in recent years is applied to the elevator group control system. For example, the technique of fuzzy control can solve many problems in which we can’t build the model or the accurate model of the controlled objects. Otherwise,the technique of fuzzy control depends on repository and it is close to the thoughts of human .We can deal with problems more efficaciously by this technique.
Based on the analysis of the development of the elevator group control system, this thesis has discussed the prospect of the application of artificial intelligence to the elevator group control system. According to some characteristics of the elevator group control system, this thesis points out the factors that influence the population performance of the system. These factors are the mainly optimized factors in the course of group control. For the need of research and modeling, this thesis analyses traffic circumstance in a building and divides it into several kinds of pattern and mainly discusses the application of fuzzy control to the traffic pattern recognition. Base on this, this thesis discusses t the application of the fuzzy control to the group control and dispatch .The results of simulation indicate that the application of fuzzy control to elevator group control system can improve the whole performance and the quality of its services evidently.
引文
[1]朱德文,杨祯山,张筠莉.智能控制电梯工程系统.北京:中国电力出版社, 2007, 1-254
[2] Kim B. C., Seong K. A., Lee H. K., Kim J. O. et al. A Fuzzy Approach to Elevator Group Control System. IEEE Transactions on System, Man, and Cybernetics, 1995, 23(6): 985-990
[3]朱德文,付国江.电梯群控技术.北京:中国电力出版社, 2006, 1-266
[4] Chen S., Nahrstedt K. Distributed quality of service routing in ad hoc network. IEEE Journal on Selected Areas in Communications, 1999, 17(8): 1488-1505
[5]宗群,曹燕飞,曲照伟.电梯群控系统中智能控制方法.电气传动, 1998, 41(3): 25-28
[6] Hitoshi A. Group supervisory control system assisted by artificial intelligence. Elevator World, 1990, 10(2): 70-80
[7]杨祯山,邵诚.电梯群控技术的现状与发展方向.控制与决策, 2005, 20(12): 1321-1331
[8] Gudwon R. , Gonmide F., Andrade Netto M. A fuzzy elevator group controller with linear context adaptation. IEEE World Congress on Computational Intelligence. 1998, 1(1): 481-486
[9] Kaneko M., Ishikawa T., Sogawa Y. Supervisory Control for Elevator Group by using Fuzzy Expert System. Industrial Electronics, Control and Instrumentation. 1997, 1(1): 370-376
[10] Imasaki N., Kubo S., Nakai S. et al. Elevator group control system tuned by a fuzzy neural network applied method. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems. 1995, 4(4): 1735-1740
[11] Ujihara H., Tsuji S. The revolutionary AI-2100 elevator-group control system andthe new intelligent option series. Mitsubishi Electric Advance, 1998, 12(45): 5-8
[12] Sakai Y., Kurosawa K. Development of elevator supervisory group control system with artificial intelligence. Hitachi Review, Review, 1984, 33(1): 25-30
[13]宋国强.智能控制技术在电梯群控系统中的应用.上海电机学院学报. 2005, 8(2): 35-38
[14]朱德文.现代电梯群控系统与人工智能技术.基础自动化, 1998, 6(5): 1-5
[15]宋涵.电梯群控系统智能控制的研究: [硕士学位论文].浙江工业大学:浙江工业大学图书馆, 2006
[16]李中华,毛宗源,邬依林.一种新的基于模糊控制的电梯群控策略.控制与决策, 2004, 19(8): 857-861
[17] Albert T. P. S., Liu S .K. An overall review of advanced elevator technologies. Elevator World, 1996, 32(21): 86-92
[18] Kenji Y. Multi-objective elevator supervisory control system with individual floor situation control. ElevatorWorld,1999, 47(5): 90-95
[19]闰冬梅,顾德英.电梯群控预约控制算法.现代电子技术, 2004, 28(12): 98-99
[20]宗群,王朝阳,岳有军等.电梯群控多目标模糊控制算法的设计.制造业自动化, 2000,22(7): 23-25
[21] Sei J. Supervisory control for elevator group by using expert system. Elevator Technology,1994,35(7):195-198
[22]唐海燕.基于模糊神经网络的电梯群优化控制研究: [硕士学位论文].哈尔滨工业大学:哈尔滨工业大学图书馆, 2006
[23]吴蕾.基于神经网络的电梯群控系统智能调度的研究: [硕士学位论文].武汉理工大学:武汉理工大学图书馆, 2007
[24]林琳.群控多目标智能最优调度算法的研究:[硕士学位论文].东北大学:东北大学图书馆, 2005
[25]唐桂忠.基于遗传算法的现代群控电梯交通客流控制: [硕士学位论文].南京工业大学:南京工业大学图书馆, 2005
[26] Barney G. C., Dos S.M. Elevator traffic analysis, design and control. London: IEEE, Peregrinus,1985
[27]马福军.电梯群控技术的研究: [硕士学位论文].浙江工业大学:浙江工业大学图书馆, 2000
[28] Cho Y. C., Kim K. H., Kwon W. H. Optimal group control of elevator systems by statistic approximation of hall call waiting times. 14th world Congress of IFAC. 1999, 103-108
[29] Siikonen M, Leppala J. Elevator traffic pattern recognition. Proc. 4th IFSA Congr, 1991, 29(8): 195-198
[30] Farag W. A, Torres G.L. A genetic based neuron-fuzzy approach for modeling and control of dynamical systems. IEEE Trans on Neural Networks, 1998, 9(5): 756-767
[31]夏斌.电梯群控系统的客流交通模式分析.硅谷, 2008, 3(24): 16-17
[32]赵长青.模式识别简述.大众科学, 2008, 19(3): 3-4
[33]殷勤业,杨宗凯,谈正,陈陵.模式识别与神经网络.北京:机械工业出版社, 1992, 1-324
[34]许力.智能控制与智能系统.北京:机械工业出版社, 2007, 1-372
[35]席爱民.模糊控制技术.西安:西安电子科技大学出版社, 2008, 1-264
[36]蔡自兴.智能控制原理与应用.北京:清华大学出版社, 2007, 1-380
[37]易继锴,侯媛彬,智能控制技术(修订版).北京:北京工业大学出版社, 2007, 1-392
[38] Siikonen M.-J. Elevator traffic simulation. Simulation, 1993 ,61(4), 257-267
[39]童铃.电梯交通流多模式预测方法的研究: [硕士学位论文].天津大学:天津大学图书馆, 2005
[40]陈元琰,邓宗明.电梯群调度的模糊神经网络方法.计算机工程, 2002, 29(12): 191-192
[41] Kim C.B., Seong K. A., Kwang H. L. et al. Design and Implementation of a Fuzzy Elevator Group Control System. IEEE Transaction on Systems, Man, and Cybernetic-Part A: Systems and Humans, 28(3): 277-285
[2] Kim B. C., Seong K. A., Lee H. K., Kim J. O. et al. A Fuzzy Approach to Elevator Group Control System. IEEE Transactions on System, Man, and Cybernetics, 1995, 23(6): 985-990
[3]朱德文,付国江.电梯群控技术.北京:中国电力出版社, 2006, 1-266
[4] Chen S., Nahrstedt K. Distributed quality of service routing in ad hoc network. IEEE Journal on Selected Areas in Communications, 1999, 17(8): 1488-1505
[5]宗群,曹燕飞,曲照伟.电梯群控系统中智能控制方法.电气传动, 1998, 41(3): 25-28
[6] Hitoshi A. Group supervisory control system assisted by artificial intelligence. Elevator World, 1990, 10(2): 70-80
[7]杨祯山,邵诚.电梯群控技术的现状与发展方向.控制与决策, 2005, 20(12): 1321-1331
[8] Gudwon R. , Gonmide F., Andrade Netto M. A fuzzy elevator group controller with linear context adaptation. IEEE World Congress on Computational Intelligence. 1998, 1(1): 481-486
[9] Kaneko M., Ishikawa T., Sogawa Y. Supervisory Control for Elevator Group by using Fuzzy Expert System. Industrial Electronics, Control and Instrumentation. 1997, 1(1): 370-376
[10] Imasaki N., Kubo S., Nakai S. et al. Elevator group control system tuned by a fuzzy neural network applied method. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems. 1995, 4(4): 1735-1740
[11] Ujihara H., Tsuji S. The revolutionary AI-2100 elevator-group control system andthe new intelligent option series. Mitsubishi Electric Advance, 1998, 12(45): 5-8
[12] Sakai Y., Kurosawa K. Development of elevator supervisory group control system with artificial intelligence. Hitachi Review, Review, 1984, 33(1): 25-30
[13]宋国强.智能控制技术在电梯群控系统中的应用.上海电机学院学报. 2005, 8(2): 35-38
[14]朱德文.现代电梯群控系统与人工智能技术.基础自动化, 1998, 6(5): 1-5
[15]宋涵.电梯群控系统智能控制的研究: [硕士学位论文].浙江工业大学:浙江工业大学图书馆, 2006
[16]李中华,毛宗源,邬依林.一种新的基于模糊控制的电梯群控策略.控制与决策, 2004, 19(8): 857-861
[17] Albert T. P. S., Liu S .K. An overall review of advanced elevator technologies. Elevator World, 1996, 32(21): 86-92
[18] Kenji Y. Multi-objective elevator supervisory control system with individual floor situation control. ElevatorWorld,1999, 47(5): 90-95
[19]闰冬梅,顾德英.电梯群控预约控制算法.现代电子技术, 2004, 28(12): 98-99
[20]宗群,王朝阳,岳有军等.电梯群控多目标模糊控制算法的设计.制造业自动化, 2000,22(7): 23-25
[21] Sei J. Supervisory control for elevator group by using expert system. Elevator Technology,1994,35(7):195-198
[22]唐海燕.基于模糊神经网络的电梯群优化控制研究: [硕士学位论文].哈尔滨工业大学:哈尔滨工业大学图书馆, 2006
[23]吴蕾.基于神经网络的电梯群控系统智能调度的研究: [硕士学位论文].武汉理工大学:武汉理工大学图书馆, 2007
[24]林琳.群控多目标智能最优调度算法的研究:[硕士学位论文].东北大学:东北大学图书馆, 2005
[25]唐桂忠.基于遗传算法的现代群控电梯交通客流控制: [硕士学位论文].南京工业大学:南京工业大学图书馆, 2005
[26] Barney G. C., Dos S.M. Elevator traffic analysis, design and control. London: IEEE, Peregrinus,1985
[27]马福军.电梯群控技术的研究: [硕士学位论文].浙江工业大学:浙江工业大学图书馆, 2000
[28] Cho Y. C., Kim K. H., Kwon W. H. Optimal group control of elevator systems by statistic approximation of hall call waiting times. 14th world Congress of IFAC. 1999, 103-108
[29] Siikonen M, Leppala J. Elevator traffic pattern recognition. Proc. 4th IFSA Congr, 1991, 29(8): 195-198
[30] Farag W. A, Torres G.L. A genetic based neuron-fuzzy approach for modeling and control of dynamical systems. IEEE Trans on Neural Networks, 1998, 9(5): 756-767
[31]夏斌.电梯群控系统的客流交通模式分析.硅谷, 2008, 3(24): 16-17
[32]赵长青.模式识别简述.大众科学, 2008, 19(3): 3-4
[33]殷勤业,杨宗凯,谈正,陈陵.模式识别与神经网络.北京:机械工业出版社, 1992, 1-324
[34]许力.智能控制与智能系统.北京:机械工业出版社, 2007, 1-372
[35]席爱民.模糊控制技术.西安:西安电子科技大学出版社, 2008, 1-264
[36]蔡自兴.智能控制原理与应用.北京:清华大学出版社, 2007, 1-380
[37]易继锴,侯媛彬,智能控制技术(修订版).北京:北京工业大学出版社, 2007, 1-392
[38] Siikonen M.-J. Elevator traffic simulation. Simulation, 1993 ,61(4), 257-267
[39]童铃.电梯交通流多模式预测方法的研究: [硕士学位论文].天津大学:天津大学图书馆, 2005
[40]陈元琰,邓宗明.电梯群调度的模糊神经网络方法.计算机工程, 2002, 29(12): 191-192
[41] Kim C.B., Seong K. A., Kwang H. L. et al. Design and Implementation of a Fuzzy Elevator Group Control System. IEEE Transaction on Systems, Man, and Cybernetic-Part A: Systems and Humans, 28(3): 277-285