A type-2 self-organizing neural fuzzy system and its FPGA implementation

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 38, Issue 6, 2008, Pages 1537-1548

  Juang, Chia Feng ^a   Tsao, Yu Wei ^b  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

^b INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE   (Taiwan)

Author keywords

Fuzzy chip; Fuzzy neural networks (FNNs); Structure learning; System identification; Type 2 fuzzy systems

Indexed keywords

CLUSTERING ALGORITHMS; CONTROL THEORY; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); FUZZY LOGIC; FUZZY NEURAL NETWORKS; FUZZY SETS; FUZZY SYSTEMS; HARDWARE; NEURAL NETWORKS; NONLINEAR SYSTEMS;

COMPLEX COMPUTATIONS; CONTROL PROBLEMS; DESIGNED CIRCUITS; FIELD-PROGRAMMABLE GATE ARRAYS; FPGA IMPLEMENTATIONS; FUZZY CHIP; HARDWARE IMPLEMENTATIONS; IMPLEMENTATION TECHNIQUES; INPUT SPACES; KALMAN FILTER ALGORITHMS; LEARNING ABILITIES; MAMDANI TYPES; NEURAL FUZZY SYSTEMS; NONLINEAR SYSTEM IDENTIFICATIONS; PARAMETER IDENTIFICATIONS; SELF-ORGANIZING; STRUCTURE IDENTIFICATIONS; STRUCTURE LEARNING; SYSTEM IDENTIFICATION; TRAINING DATUMS; TYPE-2 FUZZY SYSTEMS;

IDENTIFICATION (CONTROL SYSTEMS);

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; FEEDBACK SYSTEM; FUZZY LOGIC; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; FEEDBACK; FUZZY LOGIC; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 57049085724     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2008.927713     Document Type: Article

References (36)

1. N. N. Karnik, J. M. Mendel, and Q. Liang, "Type-2 fuzzy logic systems," IEEE Trans. Fuzzy Syst., vol. 7, no. 6, pp. 643-658, Dec. 1999.
2. Q. Liang and J. M. Mendel, "Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters," IEEE Trans. Fuzzy Syst., vol. 8, no. 5, pp. 551-563, Oct. 2000.
3. Q. Liang and J. M. Mendel, "MPEG VBR video traffic modeling and classification using fuzzy technique," IEEE Trans. Fuzzy Syst., vol. 9, no. 1, pp. 183-193, Feb. 2001.
4. H. B. Mitchell, "Pattern recognition using type-II fuzzy sets," Inf. Sci., vol. 170, no. 2-4, pp. 409-418, Feb. 2005.
5. J. Zeng and Z. Q. Liu, "Type-2 fuzzy hidden Markov models and their application to speech recognition," IEEE Trans. Fuzzy Syst., vol. 14, no. 3, pp. 454-467, Jun. 2006.
6. C. Hwang and F. C.-H. Rhee, "Uncertain fuzzy clustering: Interval type-2 fuzzy approach to C-means," IEEE Trans. Fuzzy Syst., vol. 15, no. 1, pp. 107-120, Feb. 2007.
7. P. Melin and O. Castillo, "A new method for adaptive control of nonlinear plants using type-2 fuzzy logic and neural networks," J. Gen. Syst., vol. 33, no. 2/3, pp. 289-304, Apr.-Jun. 2004.
8. H. Hagras, "A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots," IEEE Trans. Fuzzy Syst., vol. 12, no. 4, pp. 524-539, Aug. 2004.
9. J. M. Mendel and R. I. John, "Type-2 fuzzy sets made simple," IEEE Trans. Fuzzy Syst., vol. 10, no. 2, pp. 117-127, Apr. 2002.
10. J. M. Mendel, Uncertain Rule-Based Fuzzy Logic System: Introduction and New Directions. Upper Saddle River, NJ: Prentice-Hall, 2001.
11. Q. Liang and J. M. Mendel, "Interval type-2 fuzzy logic systems: Theory and design," IEEE Trans. Fuzzy Syst., vol. 8, no. 5, pp. 535-550, Oct. 2000.
12. C. H. Lee, Y. C. Lin, and W. Y. Lai, "Systems identification using type-2 fuzzy neural network (type-2 FNN) systems," in Proc. IEEE Int. Symp. Comput. Intell. Robot. Autom., 2003, vol. 3, pp. 1264-1269.
13. C. H. Wang, C. S. Cheng, and T. T. Lee, "Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 3, pp. 1462-1477, Jun. 2004.
14. H. Hagras, "Comments on 'dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)'," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 36, no. 5, pp. 1206-1209, Oct. 2006.
15. J. M. Mendel, "Computing derivatives in interval type-2 fuzzy logic systems," IEEE Trans. Fuzzy Syst., vol. 12, no. 1, pp. 84-98, Feb. 2004.
16. G. M. Mendez and O. Castillo, "Interval type-2 TSK fuzzy logic systems using hybrid learning algorithm," in Proc. IEEE Int. Conf. Fuzzy Syst., May 22-25, 2005, pp. 230-235.
17. H. Eichfeld, T. Künemund, and M. Menke, "A 12b general-purpose fuzzy logic controller chip," IEEE Trans. Fuzzy Syst., vol. 4, no. 4, pp. 460-475, Nov. 1996.
18. M. J. Patyra, J. L. Grantner, and K. Koster, "Digital fuzzy logic controller: Design and implementation," IEEE Trans. Fuzzy Syst., vol. 4, no. 4, pp. 439-459, Nov. 1996.
19. G. Ascia, V. Catania, and M. Russo, "VLSI hardware architecture for complex fuzzy systems," IEEE Trans. Fuzzy Syst., vol. 7, no. 5, pp. 553-569, Oct. 1999.
20. J. M. Jou, P. Y. Chen, and S. F. Yang, "An adaptive fuzzy logic controller: Its VLSI architecture and applications," IEEE Trans. Very Large Scale Integr. Syst., vol. 8, no. 1, pp. 52-60, Feb. 2000.
21. V. Salapura, "A fuzzy RISC processor," IEEE Trans. Fuzzy Syst., vol. 8, no. 6, pp. 781-790, Dec. 2000.
22. G. Louverdis and I. Andreadis, "Design and implementation of a fuzzy hardware structure for morphological color image processing," IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 3, pp. 277-288, Mar. 2003.
23. M. A. Manzoul and D. Jayabharathi "FPGA for fuzzy controllers," IEEE Trans. Syst., Man, Cybern., vol. 25, no. 1, pp. 213-216, Jan. 1995.
24. D. Kim, "An implementation of fuzzy logic controller on the reconfigurable FPGA system," IEEE Trans. Ind. Electron., vol. 47, no. 3, pp. 703-715, Jun. 2000.
25. C. F. Juang and C. H. Hsu, "Temperature control by chip-implemented adaptive recurrent fuzzy controller designed by evolutionary algorithm," IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 52, no. 11, pp. 2376-2384, Nov. 2005.
26. C. F. Juang and J. S. Chen, "Water bath temperature control by a recurrent fuzzy controller and its FPGA implementation," IEEE Trans. Ind. Electron., vol. 53, no. 3, pp. 941-949, Jun. 2006.
27. Q. Cao, M. H. Lim, J. H. Li, Y. S. Ong, and W. L. Ng, "A context switchable fuzzy inference chip," IEEE Trans. Fuzzy Syst., vol. 14, no. 4, pp. 552-567, Aug. 2006.
28. S. Sanchez-Solano, A. J. Cabrera, I. Baturone, F. J. Moreno-Velo, and M. Brox, "FPGA implementation of embedded fuzzy controllers for robotic applications," IEEE Trans. Ind. Electron., vol. 54, no. 4, pp. 1937-1945, Aug. 2007.
29. M. A. Melgarejo and C. A. Pena-Reyes, "Hardware architecture and FPGA implementation of a type-2 fuzzy system," in Proc. ACM GLSVLSI, Boston, MA, 2004, pp. 458-461.
30. M. A. Melgarejo, R. A. Garcia, and C. A. Pena-Reyes, "Pro-two: A hardware based platform for real time type-2 fuzzy inference," in Proc. IEEE Int. Conf. Fuzzy Syst., Jul. 2004, vol. 2, pp. 977-982.
31. S. H. Huang and Y. R. Chen, "VLSI implementation of type-2 fuzzy inference processor," in Proc. IEEE Int. Symp. Circuits Syst., May 2005, vol. 4, pp. 3307-3310.
32. M. Melgarejo and C. A. Pena-Reyes, "Implementing interval type-2 fuzzy processors," IEEE Comput. Intell. Mag., vol. 2, no. 1, pp. 63-71, Feb. 2007.
33. H. Wu and J. M. Mendel, "Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems," IEEE Trans. Fuzzy Syst., vol. 10, no. 5, pp. 622-639, Oct. 2002.
34. C. F. Juang and C. T. Lin, "An on-line self- constructing neural fuzzy inference network and its applications," IEEE Trans. Fuzzy Syst., vol. 6, no. 1, pp. 12-32, Feb. 1998.
35. C. J. Lin and C. T. Lin, "An ART-based fuzzy adaptive learning control network," IEEE Trans. Fuzzy Syst., vol. 5, no. 4, pp. 477-496, Nov. 1997.
36. L. X. Wang and J. M. Mendel, "Generating fuzzy rules by learning from examples," IEEE Trans. Syst., Man, Cybern., vol. 22, no. 6, pp. 1414-1427, Nov./Dec. 1992.