An Artificial Immune System for Frequency-Variable Air Conditioner

Article Preview

Abstract:

It is common to control the Frequency-variable air conditioner (A/C) by using PID controller. However, an arithmetic based on artificial immune system was proposed. The immune system of organism was analyzed, and an architecture of the arithmetic was designed. The A/C behaviors were expressed by antibodies, a concentration model of antibody was built, and rules of A/C behaviors could be obtained by the antibody concentration. the initial immune response arithmetic and the secondary immune response arithmetic were designed, which were used to memorized normal behaviors and detect abnormal behaviors. Experiments show that the scheme is capable of adapting to system variation. The system can obtain the stable condition with good convergence even high temperature of 45°C

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1449-1452

Citation:

Online since:

October 2010

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2010 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Astrom K, Hagglund T. PID controller: theory, design, and tuning . New York: ISA, (1995).

Google Scholar

[2] Tzafestas S G. Fuzzy systems and fuzzy expert control: An overview . Knowledge Engineering Review, (1994).

Google Scholar

[3] Tzafestas S G, Papanikolopoulos N P. Incremental fuzzy expert PID control ,. IEEE Transactions on Industrial Electronics, 1990, vol, 37: pp, 365-371.

DOI: 10.1109/41.103431

Google Scholar

[4] He S Z, Tan S H , Xu F L , et al . Fuzzy self-tuning of PID controllers, . Fuzzy Sets and Systems, 1993, vol, pp, 56 : 372: 46.

DOI: 10.1016/0165-0114(93)90183-i

Google Scholar

[5] Y. Zhao Z Y, Tomizuka M, Isaka S. Fuzzy gain scheduling of PID controllers, . IEEE Transactions on Systems, Man, and Cybernetics , 1993 , vol, 23, pp: 1392-1398.

DOI: 10.1109/21.260670

Google Scholar

[6] Visioli A. Fuzzy logic based set point weight turning of PID controller, . IEEE Transactions on Systems, Man, and Cybernetics (Part A: Systems and Humans), 1999, vol, 29, pp: 587-592.

DOI: 10.1109/3468.798062

Google Scholar

[7] Chen J.L., Chen J.W., Chen H.C., Chang Y.C., Yang,C. C, Liaw C.M. Front-end low-frequency switched-mode rectifier and its control for permanent-magnet synchronous-motor drive, IEEE Proceedings Electric Power Applications, 2005, vol, 7, pp: 905~914.

DOI: 10.1049/ip-epa:20050090

Google Scholar

[8] Yang Ming, Gao Yang, Xu Dian-Guo, Yu Yong. On-line self-tuning of PI controller for PMSM drives based on the iterative learning control", APEC, 05, 2005, pp: 1889~1893.

DOI: 10.1109/apec.2005.1453309

Google Scholar

[9] Guney,I., Oguz,Y., Serteller,F. Dynamic behaviour model of permanent magnet synchronous motor fed by PWM inverter and fuzzy logic controller for stator phase current, flux and torque control of PMSM", IEMDC, 01 2001, pp: 479~485.

DOI: 10.1109/iemdc.2001.939349

Google Scholar

[10] Xiaohui Ge, Jin Huang. Chaos Control of Permanent Magnet Synchronous Motor", ICEMS, 05 2005, pp: 484~488.

DOI: 10.1109/icems.2005.202575

Google Scholar

[11] Monajemy,R., Krishnan,R. Control and dynamics of constant-power-loss-based operation of permanent-magnet synchronous motor drive system, IEEE Transactions on Industrial Electronics, 2001vol, 8pp: 839~844.

DOI: 10.1109/41.937417

Google Scholar

[12] Qiu,A., Bin Wu, Kojori,H. Sensorless control of permanent magnet synchronous motor using extended Kalman filter, Canadian Conference on Electrical and Computer Engineering, 2004, p.1557~1562.

DOI: 10.1109/ccece.2004.1349704

Google Scholar