The Resistance-Heated Furnace Temperature Control Based on CMAC-Fuzzy Immune PID Control

Abstract:

The control demand can not be satified by general PID algorithm because of time-change, nonlinear, uncertainty of controlled parameters in control process of the resistance-heated furnace. Based on regulative fuction of bilogic immune feedback response and characteristic of overhang nonlinear fuction with fuzzy discursion, and combining the advantages of CMAC(Cerebellar Model Articulation Controller), the CMAC-Fuzzy Immune-PID control strategy is applied to temperature control system of the resistance-heated furnace. Simulation study results show that control systems based on this method can attain high quality, is capable of adapting itself to variations of the control object’s parameters, and is featured by strong robustness and self-adaptability.

• Periodical: Applied Mechanics and Materials (Volumes 29-32)
• Pages: 407-413
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.29-32.407
• Online since: August 2010
• Authors: Ding Du Wen
• Keywords: Cerebella Model Articulation Control (CMAC), Fuzzy Logic, Immune PID Control, Resistance-Heated Furnace

References

[1] Huailin Shu, and Youguo Pi, PID neural netwrks for time-delay systems, Computers and Chemical Engineering, vol. 28, 2000, pp.859-862.

DOI: 10.1016/s0098-1354(00)00340-9

[2] Zhang Weiguo, and Yang Yanzhong, Fuzzy Control Ttheory and Application, edtied by House of N. P. University Publications (2005), China.

[3] J.S. Albus, A new approach to manipulator control: the cerebellar model articulation controller (CMAC) , Trans. ASME J. Dyn. Syst. Meas. Contr, 1975, pp.220-227.

DOI: 10.1115/1.3426922

[4] J.S. Albus, Data storage in the cerebellar model articulation controller (CMAC), Trans. ASME J. Dyn. Syst. Meas. Contr, 1975, pp.228-233.

DOI: 10.1115/1.3426923

[5] F.G. Harmon, A.A. Frank, and S.S. Joshi, The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network, Neural Networks, vol. 18, 2005, pp.772-780.

DOI: 10.1016/j.neunet.2005.06.030

[6] E. Mese, A rotor position estimator for switched reluctance motors using CMAC, Energy Convers Managem, vol. 44, 2003, pp.1229-1245.

DOI: 10.1016/s0196-8904(02)00138-3

[7] W.T. Miller, R.P. Hewes, and F.H. Glanz, L.G. Graft, Real-time dynamic control of an industrial manipulator using a neural-networkbased learning controller, IEEE Trans. Robot Autom, 1990, pp.1-6.

DOI: 10.1109/70.88112

[8] A. Kolcz, and N.M. Allinson, Application of the CMAC input encoding scheme in the N-tuple approximation network, IEE Proc. Computer Digital Tech, vol. 41, 1994, pp.177-183.

DOI: 10.1049/ip-cdt:19941004

[9] F.H. Glanz, W.T. Miller, and L.G. Graft, An overview of the CMAC neural network, Proc. IEEE Neural Networks Ocean Eng, vol. 131, 1991, pp.301-308.

DOI: 10.1109/icnn.1991.163366

[10] C.P. Hung, and M.H. Wang, Diagnosis of incipient faults in power transformers using CMAC neural network approach, Electric Power Syst. Res, vol. 71, 2004, pp.235-244.

DOI: 10.1016/j.epsr.2004.01.019

[11] S. Wang, and Z. Jiang, Valve fault detection and diagnosis based on CMAC neural networks, Energy Build, vol. 36, 2004, pp.599-610.

DOI: 10.1016/j.enbuild.2004.01.037

[12] Kim D. H, Tuning of a PID controller using immune network model and fuzzy set, IEEE International Symposium on Industrial Electronics, 2001, pp.1656-1661.

DOI: 10.1109/isie.2001.931956

[13] Takahashi K, and Yamada T, Application of an immune feedback mechanism to control systems, JSME Int J, Series C, vol. 41, 1998, pp.184-191.

DOI: 10.1299/jsmec.41.184

[14] WANG Dong-feng, and HAN Pu, Variable arguments PID control for main steam temperature system based on immune genetic optimization, Proceedings of the CSEE, vol. 23, 2003, pp.212-217.

[15] J. Wu, and F. Pratt, Self-organizing CMAC neural networks and adaptive dynamic control, Proc. IEEE Int. Symp. on Intell. Contr. / Intell. Systems and Semiotics, Cambridge, MA, 1999, pp.259-265.

DOI: 10.1109/isic.1999.796665

[16] Wen Ding-du, Research Combined with for a Kindon a Novel Control Strategy Fuzzy-Dahlin of System with Time-delay, Industrial Instrumentation and Automation, China, vol. 196, 2007, pp.3-5.