住宅智能控制器及空调器最佳起停控制算法研究
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摘要
本文在现有的智能住宅的产品基础上,分析了智能住宅在国内外的发展现状和趋势。同时,指出了由于目前价格问题是限制智能住宅产品在国内推广的主要原因。为此,本课题分析了智能住宅控制器的功能后,提出了一种新型的住宅控制器的设计思路,在实现住宅控制器的基本功能的基础上,最大程度地减少成本。
本文选用了以电力线作为智能住宅控制器之间的通信介质,并选取了基于DTMF编码的电力线载波通信方式。这样一方面不必另外布线,可以利用住宅内已有的照明电力线路;另一方面采用这种编码方式完全可以满足家庭控制系统中传输控制信号的要求。本文重点设计了电力线载波通信的硬件结构和软件程序流程的设计过程,以及相应的防干扰措施。
本文设计了一种基于Elman神经网络的空调最佳起停控制算法,不仅减少智能住宅中系统设置的复杂性,还达到了节能的效果。在住宅智能控制系统的基础上,以两级优先级的方式来控制空调:手动方式为第一优先级;在无手动控制的情况下,节点控制器按照控制算法实行自动控制。这样既减少了用户繁琐的系统设置操作,增加了智能住宅产品的通用性,又可以在满足舒适性的前提下最大程度地达到节能的效果。
最后本文提出了基于Elman神经网络的空调最佳起停控制算法的基本思想。通过遗传算法来优化Elman神经网络的初始权值阀值,并将训练好的网络用于空调的控制。同时结合空调房间的数学模型,在Simulink环境下建立了整个系统的模型,并通过系统仿真验证了这一方法的可行性。
In this article, the development and direction of the Intelligent Residence is analyzed, based on the product of the Intelligent Residence nowadays. Meanwhile, the article points out that the mostly causation of restricting the popularize of the Intelligent Residence is the price. To resolve this problem, after analyzing the basic function of Intelligent Residence Controller, the article brings forward s newly designed Residence Controller. The Controller not only actualizes the basic function, but also reduces the cost whole hog.
First, the power line is chosen as communication medium between Intelligent Residence Controllers, and DTMF is selected as decoding and encoding method. In this way, it is needn’t to wiring additionally, the lighting and power line can that already exist in the residence be used. On the other hand, DTMF can meet the demand for transmitting control signal in residence. This article mostly emphasizes the design for the hardware structure and software flow of power line carrier, and relevant measure for anti-jamming.
To predigest the settings of intelligent residence and achieve the effect of energy-saving, a new way is developed to control air-condition best fit for the time-schedule based on Elman-NN, and also can save energy. According to Intelligent Residence Control System, A 2- PRI is designed to control air-condition: first PRI is manual control. If there is no manual control, automation, which is according to control strategy is activated. By this way, it can make the product more popular and save more energy at the precondition of comfort.
At last, a tactic for air-condition based on Elman-NN’s control is introduced. Elman-NN’s initial weight matrix is optimized through GA, then the trained-network is used to control the air-condition. Combining with the model of air-condition, after emulated in Matlab/Simulink, it is proved to be work well.
本文选用了以电力线作为智能住宅控制器之间的通信介质,并选取了基于DTMF编码的电力线载波通信方式。这样一方面不必另外布线,可以利用住宅内已有的照明电力线路;另一方面采用这种编码方式完全可以满足家庭控制系统中传输控制信号的要求。本文重点设计了电力线载波通信的硬件结构和软件程序流程的设计过程,以及相应的防干扰措施。
本文设计了一种基于Elman神经网络的空调最佳起停控制算法,不仅减少智能住宅中系统设置的复杂性,还达到了节能的效果。在住宅智能控制系统的基础上,以两级优先级的方式来控制空调:手动方式为第一优先级;在无手动控制的情况下,节点控制器按照控制算法实行自动控制。这样既减少了用户繁琐的系统设置操作,增加了智能住宅产品的通用性,又可以在满足舒适性的前提下最大程度地达到节能的效果。
最后本文提出了基于Elman神经网络的空调最佳起停控制算法的基本思想。通过遗传算法来优化Elman神经网络的初始权值阀值,并将训练好的网络用于空调的控制。同时结合空调房间的数学模型,在Simulink环境下建立了整个系统的模型,并通过系统仿真验证了这一方法的可行性。
In this article, the development and direction of the Intelligent Residence is analyzed, based on the product of the Intelligent Residence nowadays. Meanwhile, the article points out that the mostly causation of restricting the popularize of the Intelligent Residence is the price. To resolve this problem, after analyzing the basic function of Intelligent Residence Controller, the article brings forward s newly designed Residence Controller. The Controller not only actualizes the basic function, but also reduces the cost whole hog.
First, the power line is chosen as communication medium between Intelligent Residence Controllers, and DTMF is selected as decoding and encoding method. In this way, it is needn’t to wiring additionally, the lighting and power line can that already exist in the residence be used. On the other hand, DTMF can meet the demand for transmitting control signal in residence. This article mostly emphasizes the design for the hardware structure and software flow of power line carrier, and relevant measure for anti-jamming.
To predigest the settings of intelligent residence and achieve the effect of energy-saving, a new way is developed to control air-condition best fit for the time-schedule based on Elman-NN, and also can save energy. According to Intelligent Residence Control System, A 2- PRI is designed to control air-condition: first PRI is manual control. If there is no manual control, automation, which is according to control strategy is activated. By this way, it can make the product more popular and save more energy at the precondition of comfort.
At last, a tactic for air-condition based on Elman-NN’s control is introduced. Elman-NN’s initial weight matrix is optimized through GA, then the trained-network is used to control the air-condition. Combining with the model of air-condition, after emulated in Matlab/Simulink, it is proved to be work well.
引文
1陈长征,唐忠.智能住宅系统功能分析.基础自动化. 2001,3(8):4-6
2 Rafael Sacks, Abraham Warszawski. A Project Model for An Automated Building System: Design and Planning Phases. Automation in Construction. 1997, (7): 21-34
3杜正强,冯绍兵,朱学莉.家庭设施控制装置的硬件设计.工程设计CAD与智能建筑. 2002, (8): 68-71
4张瑞武.智能建筑.清华大学出版社, 1996:210-245
5 T. Derek, J. Clements-Croome. What do We Mean by Intelligent Buildings? Automation in Construction. 1997, (6): 395-400
6 Steven T. Bushby. BACnet: A Standard Communication Infrastructure for Intelligent Buildings. Automation in Construction. 1997, (6): 529-540
7蒋小洛.智能建筑的发展趋势.工程设计CAD与智能建筑. 2002, (7): 42-45
8 Chao-Lin Wu, Wei-Chen Wang, Li-Chen Fu. Mobile Agent based Integrated Control Architecture for Home Automation System. Intelligent Robots and Systems. 2004, (9): 330-338
9文国良,姜袁.建筑电气的控制总线系统与应用.武汉水利电力大学(宜昌)学报. 2000,22(3):224-227
10齐维贵,朱学莉,邵仙鹤,喻言.基于LONWORKS技术的家庭控制装置的研究.哈尔滨建筑大学学报. 2002,35(1):90-93
11 D. L. Loveday, G. S. Virk, J. Y. M. Cheung, D. Azzi. Intelligence in Buildings: The Potential of Advanced Modelling. Automation in Construction. 1997, (6): 447-461
12马鸿雁,陈志新,何伟良.我国智能化小区发展综述.北京建筑工程学院学报. 2003,19(1):88-93
13智能建筑技术与应用.建设部科学技术委员会智能建筑技术开发推广中心. 2001:3-5
14 Oran Simic, Vladan Devedzic. Building An Intelligent System using Modern Internet Technologies. Expert Systems with Applications. 2003, (25): 231-246
15佟勇. 21世纪智能住宅建设的发展趋势.山西建筑. 2005,31(22):33-34
16段培永,曹建荣.小区智能化集成系统的结构与功能.青岛大学学报.2002,17(3):68-72
17 Topalis E, Orphanos G, Koubias S, Papadopoulos G. A Generic Network Management Architecture targeted to Support Home Automation Networks and Home Internet Connectivity. Consumer Electronics. 2002, (2): 125-131
18 N. Miura, H. Sato, H. Narita. Automatic Meter Reading System by Power Line Carrier Communications. Proc. Inst. Elect. Eng. 1990:25-31
19王维新,常本康.智能建筑中空调系统的综合节能.南京理工大学学报. 1999,23(5):450-453
20秦文华,田海峰.低压电力线载波通信中远程数据采集.电子技术. 2005, (6): 58-61
21 D. Clark. Power Line Communications. IEEE Internet Computing. 1998, (1): 360-365
22陆宁,梁坚,尤晋元.智能楼宇管理系统的设计与实现.上海交通大学学报. 2000(7):928-931
23张锡林,卢正强,李仕良.有线电视网作为智能小区信息传输方法的研究.计算机与信息技术. 2007, (7): 67-67
24 George Lawton. New Technologies Take the Network Home. IEEE Computer, March 1999,32(3):11-14
25滕志军.基于PLC的住宅小区智能化设计.电子技术. 2006, (7): 43-45
26肖寒春,吕翊.智能建筑中的通信技术.建筑电气. 2001, (4): 12-18
27彭会萍.基于蓝牙技术的智能住宅网络设计研究.电脑开发与应用. 2005,18(3):24-25
28 O'Leary, P. Pauritsch, M. Maloberti, F. An Oversampling-based DTMF Generator. IEEE Transactions on Communications. 1991,39(8):1189-1191
29刘玉忠.电力线载波通信技术分析.太原科技. 2005, (2): 32-36
30肖海荣,杨金清.基于DTMF技术的电力线载波系统设计.山东交通学院学报. 2002,10(4):58-61
31李林.智能大厦系统工程.电子工业出版社, 1998:222-241
32尉迟斌,卢士浚,周祖毅.实用制冷与空调工程手册.机械工业出版社, 2001:78-119
33 Robert N. Lea. An HVAC Fuzzy Logic Zone Control System and Perfomance Results. 1996 5th IEEE International Conference, Part3. 1996:2175-2180
34 Qiao Guo, Qing-wei Xu. Optimun Energy Management of the Central Air-Conditioning System in Intelligent Buildings. Journal of Beijing Institute of Technology. 2002,3(11):298-301
35 M. C. Jean. Scientific Basis of Air Conditioning. Applied Science Publishers Ltd, 1981:15-103
36李吉生.建筑能源管理控制系统的研究.清华大学, 1995:21-30
37 Yu-Xue Sun, An-Hou Long, Jian-Wei Peng. Application of Artificial Neural Network to the Research of Formation Damage. Proceedings of the Third International Conference on Machine Learning and Cybernetics. Shanghai, 2004:3484-3487
38尹权,韩生廉.电流/电压转换芯片MAX472在电流检测器中的应用.电子设计应用. 2003, (3): 81-82
39程菊花.基于单片机的电力线载波通信系统.浙江树人大学学报. 2005,5(4):97-109
40郑新华.电力线载波通讯芯片市场与应用前景.今日电子. 1999, (10): 16-17
41 Sonali Bagchi, Sanjit K. Mitra. Efficient Robust DTMF Decoding using the Subband NDFT. Signal Processing. 1997, (56): 255-267
42张雪萍,刘作军,李练兵.智能楼宇定风量空调系统的启停控制.河北工业大学学报. 2001,30(6):98-101
43 R. J. Williams, D. Zipser. Alearning Algorithm for Continually Running fully Recurrent Neural Networks. Neural Computation. 1989,1(1):270-280
44高隽.人工神经网络原理及仿真实例.机械工业出版社, 2003:1-22
45 K. S. Narendra, K. Parthasarathy. Gradient Methods for the Optimization of Dynamical Systems Containing Neural Networks. IEEE Transactions on Neural Networks, 1991, (2): 252-262
46 J. L. Elman. Finding Structure in Time. Cognitive Science. 1990,1(14):179-211
47 A. Waibel, T. Hanazawa, G. Hinton, K. Shiton, K. J. Lang. Phoneme Recognition using Time-delay Neural Networks. IEEE Transactions on Acoustics, Speech and Signal Processing. 1989, (37): 328-339
48 Z.米凯利维茨.演化程序—遗传算法和数据编码的结合.周家驹,何险峰译.科学出版社. 2000:14-17
49雷英杰. MATLAB遗传算法工具箱及应用.西安电子科技大学出版社. 2006:62-94
50李国勇.智能控制及其MATLAB实现.电子工业出版社. 2005:174-176
2 Rafael Sacks, Abraham Warszawski. A Project Model for An Automated Building System: Design and Planning Phases. Automation in Construction. 1997, (7): 21-34
3杜正强,冯绍兵,朱学莉.家庭设施控制装置的硬件设计.工程设计CAD与智能建筑. 2002, (8): 68-71
4张瑞武.智能建筑.清华大学出版社, 1996:210-245
5 T. Derek, J. Clements-Croome. What do We Mean by Intelligent Buildings? Automation in Construction. 1997, (6): 395-400
6 Steven T. Bushby. BACnet: A Standard Communication Infrastructure for Intelligent Buildings. Automation in Construction. 1997, (6): 529-540
7蒋小洛.智能建筑的发展趋势.工程设计CAD与智能建筑. 2002, (7): 42-45
8 Chao-Lin Wu, Wei-Chen Wang, Li-Chen Fu. Mobile Agent based Integrated Control Architecture for Home Automation System. Intelligent Robots and Systems. 2004, (9): 330-338
9文国良,姜袁.建筑电气的控制总线系统与应用.武汉水利电力大学(宜昌)学报. 2000,22(3):224-227
10齐维贵,朱学莉,邵仙鹤,喻言.基于LONWORKS技术的家庭控制装置的研究.哈尔滨建筑大学学报. 2002,35(1):90-93
11 D. L. Loveday, G. S. Virk, J. Y. M. Cheung, D. Azzi. Intelligence in Buildings: The Potential of Advanced Modelling. Automation in Construction. 1997, (6): 447-461
12马鸿雁,陈志新,何伟良.我国智能化小区发展综述.北京建筑工程学院学报. 2003,19(1):88-93
13智能建筑技术与应用.建设部科学技术委员会智能建筑技术开发推广中心. 2001:3-5
14 Oran Simic, Vladan Devedzic. Building An Intelligent System using Modern Internet Technologies. Expert Systems with Applications. 2003, (25): 231-246
15佟勇. 21世纪智能住宅建设的发展趋势.山西建筑. 2005,31(22):33-34
16段培永,曹建荣.小区智能化集成系统的结构与功能.青岛大学学报.2002,17(3):68-72
17 Topalis E, Orphanos G, Koubias S, Papadopoulos G. A Generic Network Management Architecture targeted to Support Home Automation Networks and Home Internet Connectivity. Consumer Electronics. 2002, (2): 125-131
18 N. Miura, H. Sato, H. Narita. Automatic Meter Reading System by Power Line Carrier Communications. Proc. Inst. Elect. Eng. 1990:25-31
19王维新,常本康.智能建筑中空调系统的综合节能.南京理工大学学报. 1999,23(5):450-453
20秦文华,田海峰.低压电力线载波通信中远程数据采集.电子技术. 2005, (6): 58-61
21 D. Clark. Power Line Communications. IEEE Internet Computing. 1998, (1): 360-365
22陆宁,梁坚,尤晋元.智能楼宇管理系统的设计与实现.上海交通大学学报. 2000(7):928-931
23张锡林,卢正强,李仕良.有线电视网作为智能小区信息传输方法的研究.计算机与信息技术. 2007, (7): 67-67
24 George Lawton. New Technologies Take the Network Home. IEEE Computer, March 1999,32(3):11-14
25滕志军.基于PLC的住宅小区智能化设计.电子技术. 2006, (7): 43-45
26肖寒春,吕翊.智能建筑中的通信技术.建筑电气. 2001, (4): 12-18
27彭会萍.基于蓝牙技术的智能住宅网络设计研究.电脑开发与应用. 2005,18(3):24-25
28 O'Leary, P. Pauritsch, M. Maloberti, F. An Oversampling-based DTMF Generator. IEEE Transactions on Communications. 1991,39(8):1189-1191
29刘玉忠.电力线载波通信技术分析.太原科技. 2005, (2): 32-36
30肖海荣,杨金清.基于DTMF技术的电力线载波系统设计.山东交通学院学报. 2002,10(4):58-61
31李林.智能大厦系统工程.电子工业出版社, 1998:222-241
32尉迟斌,卢士浚,周祖毅.实用制冷与空调工程手册.机械工业出版社, 2001:78-119
33 Robert N. Lea. An HVAC Fuzzy Logic Zone Control System and Perfomance Results. 1996 5th IEEE International Conference, Part3. 1996:2175-2180
34 Qiao Guo, Qing-wei Xu. Optimun Energy Management of the Central Air-Conditioning System in Intelligent Buildings. Journal of Beijing Institute of Technology. 2002,3(11):298-301
35 M. C. Jean. Scientific Basis of Air Conditioning. Applied Science Publishers Ltd, 1981:15-103
36李吉生.建筑能源管理控制系统的研究.清华大学, 1995:21-30
37 Yu-Xue Sun, An-Hou Long, Jian-Wei Peng. Application of Artificial Neural Network to the Research of Formation Damage. Proceedings of the Third International Conference on Machine Learning and Cybernetics. Shanghai, 2004:3484-3487
38尹权,韩生廉.电流/电压转换芯片MAX472在电流检测器中的应用.电子设计应用. 2003, (3): 81-82
39程菊花.基于单片机的电力线载波通信系统.浙江树人大学学报. 2005,5(4):97-109
40郑新华.电力线载波通讯芯片市场与应用前景.今日电子. 1999, (10): 16-17
41 Sonali Bagchi, Sanjit K. Mitra. Efficient Robust DTMF Decoding using the Subband NDFT. Signal Processing. 1997, (56): 255-267
42张雪萍,刘作军,李练兵.智能楼宇定风量空调系统的启停控制.河北工业大学学报. 2001,30(6):98-101
43 R. J. Williams, D. Zipser. Alearning Algorithm for Continually Running fully Recurrent Neural Networks. Neural Computation. 1989,1(1):270-280
44高隽.人工神经网络原理及仿真实例.机械工业出版社, 2003:1-22
45 K. S. Narendra, K. Parthasarathy. Gradient Methods for the Optimization of Dynamical Systems Containing Neural Networks. IEEE Transactions on Neural Networks, 1991, (2): 252-262
46 J. L. Elman. Finding Structure in Time. Cognitive Science. 1990,1(14):179-211
47 A. Waibel, T. Hanazawa, G. Hinton, K. Shiton, K. J. Lang. Phoneme Recognition using Time-delay Neural Networks. IEEE Transactions on Acoustics, Speech and Signal Processing. 1989, (37): 328-339
48 Z.米凯利维茨.演化程序—遗传算法和数据编码的结合.周家驹,何险峰译.科学出版社. 2000:14-17
49雷英杰. MATLAB遗传算法工具箱及应用.西安电子科技大学出版社. 2006:62-94
50李国勇.智能控制及其MATLAB实现.电子工业出版社. 2005:174-176