智能控制在变风量空调系统控制中的应用研究
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摘要
变风量空调系统是节能性卓越、舒适性良好的全空气空调系统。其运行过程需要有适当的控制手段,以保证系统的节能效果和运行的稳定性。但针对这样复杂难控的对象,经典控制和现代控制都难以充分满足要求,所以需要借助于智能控制来全面实现。将模糊控制、神经网络控制等智能控制技术引入变风量系统控制领域,就是一项很有价值的任务。
本文不仅对其末端装置的模糊控制设计予以研究;而且探讨了采用PID神经网络解耦控制技术来消除系统机组侧2个控制回路(静压控制和新风控制)之间的耦合性。完成的主要工作如下:
1.在阐述变风量空调及其常规控制系统的基础上,分析了VAV系统的特性,指出智能控制是解决控制难题的有效途径。
2.针对变风量末端装置,应用模糊控制理论为其设计了二维模糊控制器,以完成室温控制任务。再利用Matlab进行仿真分析,结果表明:无论有无干扰,室温都能控制在设定温度值附近,其波动幅度也在允许范围内;
3、针对VAV系统的机组侧两个耦合作用强烈的控制回路,将PID神经网络解耦控制方法用来消除两者的耦合性。通过Matlab仿真来研究其效果,初步证明该技术能有效消除这两个回路间的强耦合性,保证系统稳定运行。
4、根据个人的认识和有关资料,构建了一个VAV空调系统智能控制的实验平台,以满足其研究需求。
Variable-Air-Volume Air-Conditioning System is an all air system with remarkable energy-saving and good comfort. In order to ensure the effect of energy-saving and keep system stability, its running course need proper control methods. But as to such a complex system hard to control, both classic control and modern control are difficult to fit the need fully. So it is necessary to make use of Intelligence Control to realize completely. It is a task of great significance to introducing Intelligence Control into the field of Variable-Air-Volume System control. In this thesis, I have not only studied the fuzzy control design in VAV Terminal, but also probed into eliminate the coupling between the the two loops of the unit side (pressure loop and fresh air loop) by appling PID-ANN decoupling control. The major work what have been finished are:
1. On the basis of clarifying VAV air-conditioning and its control system, I analysis the characteristics of VAV system, and point out that intelligent control is the effective way of solving its control problems.
2. I have designed a fuzzy controller of double dimensions by the fuzzy control theory for VAV Terminal, so as to accomplish the task of indoor temperature control. Then I use the simulating toolbox of matlab to Simulate and Analyse, the simulating result indicates that no matter what the influence exist or not, indoor temperature can be controlled around the set point, its fluctuation is also within the acceptable scope.
3. As to the the two loops of the unit side having strong coupling, I have applicated PID-ANN decoupling control to eliminate the coupling between them. By the simulating of Matlab to study its effect, the first step testifies that this technology can eliminate the coupling between the two loops effectively, and ensure the system operating stably.
4. According to my level of understanding and relevant information, I design a experiment installation of Intelligent control for VAV Air-Conditioning System to meet the need of research.
本文不仅对其末端装置的模糊控制设计予以研究;而且探讨了采用PID神经网络解耦控制技术来消除系统机组侧2个控制回路(静压控制和新风控制)之间的耦合性。完成的主要工作如下:
1.在阐述变风量空调及其常规控制系统的基础上,分析了VAV系统的特性,指出智能控制是解决控制难题的有效途径。
2.针对变风量末端装置,应用模糊控制理论为其设计了二维模糊控制器,以完成室温控制任务。再利用Matlab进行仿真分析,结果表明:无论有无干扰,室温都能控制在设定温度值附近,其波动幅度也在允许范围内;
3、针对VAV系统的机组侧两个耦合作用强烈的控制回路,将PID神经网络解耦控制方法用来消除两者的耦合性。通过Matlab仿真来研究其效果,初步证明该技术能有效消除这两个回路间的强耦合性,保证系统稳定运行。
4、根据个人的认识和有关资料,构建了一个VAV空调系统智能控制的实验平台,以满足其研究需求。
Variable-Air-Volume Air-Conditioning System is an all air system with remarkable energy-saving and good comfort. In order to ensure the effect of energy-saving and keep system stability, its running course need proper control methods. But as to such a complex system hard to control, both classic control and modern control are difficult to fit the need fully. So it is necessary to make use of Intelligence Control to realize completely. It is a task of great significance to introducing Intelligence Control into the field of Variable-Air-Volume System control. In this thesis, I have not only studied the fuzzy control design in VAV Terminal, but also probed into eliminate the coupling between the the two loops of the unit side (pressure loop and fresh air loop) by appling PID-ANN decoupling control. The major work what have been finished are:
1. On the basis of clarifying VAV air-conditioning and its control system, I analysis the characteristics of VAV system, and point out that intelligent control is the effective way of solving its control problems.
2. I have designed a fuzzy controller of double dimensions by the fuzzy control theory for VAV Terminal, so as to accomplish the task of indoor temperature control. Then I use the simulating toolbox of matlab to Simulate and Analyse, the simulating result indicates that no matter what the influence exist or not, indoor temperature can be controlled around the set point, its fluctuation is also within the acceptable scope.
3. As to the the two loops of the unit side having strong coupling, I have applicated PID-ANN decoupling control to eliminate the coupling between them. By the simulating of Matlab to study its effect, the first step testifies that this technology can eliminate the coupling between the two loops effectively, and ensure the system operating stably.
4. According to my level of understanding and relevant information, I design a experiment installation of Intelligent control for VAV Air-Conditioning System to meet the need of research.
引文
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[3]陆亚俊,马最良,邹平华.暖通空调[M].北京:中国建筑工业出版社,2002:1-6
[4]李金川,郑智慧.空调制冷自控系统运行与管理[M].北京,中国建材工业出版社,2002:1-10
[5]刘卫华.制冷空调新技术及进展[M].北京,机械工业出版社,2005:301-312
[6]王如竹,丁国良.最新制冷空调技术[M].北京,科学出版社,2002:382-404
[7]王静伟,李念平.建筑环境与空调节能[J].现代节能,2002,11:28-29
[8]王志勇,刘泽华,王汉青.寇广孝.基于建筑环境的空调系统设计及节能分析[J].建筑热能通风空调,2004,4:54-57
[9]董超俊.VAV控制系统的稳定性研究[J].工业仪表与自动化装置,2001,1:19~22
[10]李晓燕,闫泽生,制冷空调节能技术[M].北京,中国建筑工业出版社,2004:88-135
[11]鱼剑琳,王沣浩,建筑节能应用新技术[M].北京,化学工业出版社,2006:47-61
[12]戴斌文,狄洪发,江亿.变风量空调系统风机总风量控制方法[J].暖通空调,1999,29(3):1～6。
[13]晋欣桥,任海刚.李晓锋.多区域变风量空调系统及其分配控制研究[J].暖通空调,2001,31(6):1-4
[14]彭梦珑,屈高林.变风量(VAV)空调的新风量控制问题[J].建筑热能通风空调,2002,4:29-30
[15]晋欣桥,夏清,周兴禧,王盛卫.多区域变风量空调送风温度的优化节能控制[J].上海交通大学学报,2000,34(4):507-512
[16]孙勇,晋欣桥,杜志敏,孙金龙.变风量空调室内湿度控制分析[J].上海交通大学学报,2005,39(2):216～219
[17]Arima Masanod,Hara Elmer H,Katzberg Jack D.Fuzzy logic and rough sets controller for HVAC syslems.IEEE WESCANEX Communications,Power,and Computing,1995:133-138
[18]J.M.Sousa,R.Babuska,H.B.Verbmggen.Fuzzy predictive control applied to to an air-conditioning system[J].Control Engineering Practice,1997,5(4)::1395～1406
[19]Y.G.Piao et al.Simple fuzzy applicative control method and application in HVAC.IEEE International Conference on Fuzzy Systems,1998,1:528～532
[20]赵海波,杨昭,吴坤,神经网络模型在制冷剂物性参数计算中的应用[J].制冷与空调,2006,6(4):56-59
[22]叶华,任光胜,李夔宁.基于模糊控制的轻轨列车空调器性能测试系统[J].制冷与空调,2006,10(5):40-42
[23]王志毅,谷波,黎远光.基于模糊神经网络的热泵空调故障诊断研究[J].暖通空调,2005,35(3):15-17
[24]李涛,吴钢,陈金增,胡兴华.基于神经网络的制冷模糊控制系统仿真与优化[J].机械设计与制造,2006,4:75-77
[25]Diaz G,Sen M,Yang K T,etc.Simulation of heat exchanger performance by artificial neural networks.Int.J HVAC&RResearch,ConfRefig,Sydney,1999:435-442.
[26]吴刚,王惠玲,胡兴华,陈金增,李涛,模糊控制在制冷空调领域中的应用与发展[J]. 制冷与空调,2005,6(3):15-18。
[27]王石,易佳婷,人工神经网络—研究制冷系统的新方法[J].制冷空调,2005,5(2):47-51
[28]周兴禧,王懿,周滋峰等.变频空调器基于系统的变工况模糊控制仿真研究[J].流体机械,2000,28(7):42-46
[29]杨煜善.制冷系统新型控制方法研究—FNN控制[D].上海交通大学博士后报告,1996.4,l～5
[30]陈武,邓仕明,蔡振雄.VAV空调系统的动态建模及其送风机控制研究[J].暖通空调,2005,35(8):104-109
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