Efficient hardware/software implementation of an adaptive neuro-fuzzy system

IEEE Transactions on Fuzzy Systems

Volumn 16, Issue 3, 2008, Pages 761-778

  del Campo, Inès ^a   Echanobe, Javier ^a   Bosque, Guillermo ^a   Tarela, José Manuel ^a  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

Author keywords

Adaptive systems; Embedded systems; Field programmable gate array (FPGA); Neuro fuzzy model; System on a programmable chip (SOPC)

Indexed keywords

ADAPTIVE SYSTEMS; ARCHITECTURAL DESIGN; CELLULAR RADIO SYSTEMS; COMPUTER NETWORKS; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); FUZZY INFERENCE; FUZZY SYSTEMS; INFERENCE ENGINES; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; MULTITASKING;

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS); EMBEDDED APPLICATIONS; FIELD PROGRAMMABLE GATE ARRAY (FPGA); HIGH PRECISION; HIGH SPEEDS; NEURO FUZZY SYSTEMS; OFF-LINE TRAINING; ON CHIPS; ON-LINE PARAMETER; PARALLEL ARCHITECTURES; PIPELINED ARCHITECTURES; PROCESSOR CORES; PROPOSED ARCHITECTURES; SYSTEM-ON-A-PROGRAMMABLE-CHIP (SOPC);

FUZZY LOGIC;

EID: 45549109897     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2007.905918     Document Type: Article

References (48)

1. J. J. Buckley, "Sugeno type controllers are universal controllers," Fuzzy Sets Syst., vol. 53, no. 1, pp. 299-303, Feb. 1993.
2. S. G. Cao, N. W. Rees, and G. Feng, "Mamdani-type fuzzy controllers are universal fuzzy controllers," Fuzzy Sets Syst., vol. 123, no. 3, pp. 359-367, Nov. 2001.
3. B. Kosko, "Fuzzy systems as universal approximators," IEEE Trans. Comput., vol. 43, no. 11, pp. 1329-1333, Nov. 1994.
4. R. Rovatti, "Fuzzy piecewise multilinear and piecewise linear systems as universal approximators in sobolev norms," IEEE Trans. Fuzzy Syst., vol. 6, no. 2, pp. 235-249, May 1998.
5. L.-X.Wang and C.Wei, "Approximation accuracy of some neuro-fuzzy approaches," IEEE Trans. Fuzzy Syst., vol. 8, no. 4, pp. 470-478, Aug. 2000.
6. X.-J. Zeng and M. G. Singh, "Approximation theory of fuzzy systems-SISO case," IEEE Trans. Fuzzy Syst., vol. 2, no. 2, pp. 162-176, May 1994.
7. X.-J. Zeng and M. G. Singh, "Approximation theory of fuzzy systems-MIMO case," IEEE Trans. Fuzzy Syst., vol. 3, no. 2, pp. 219-235, May 1995.
8. X.-J. Zeng and M. G. Singh, "Approximation accuracy analysis of fuzzy systems as function approximators," IEEE Trans. Fuzzy Syst., vol. 4, no. 1, pp. 44-63, Feb. 1996.
9. J.-S. R. Jang, C.-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing. Upper Saddle River, NJ: Prentice-Hall, 1997, pt. VII.
10. A. Fanaei and M. Farrokhi, "Robust adaptive neuro-fuzzy controller for hybrid position/force control of robot manipulators in contact with unknown environment," J. Intell. Fuzzy Syst., vol. 17, no. 2, pp. 125-144, 2006.
11. S.-J. Ho, L.-S. Shu, and S.-Y. Ho, "Optimizing fuzzy neural networks for tuning PID controllers using an orthogonal simulated annealing algorithm OSA," IEEE Trans. Fuzzy Syst., vol. 14, no. 3, pp. 421-434, Jun. 2006.
12. H. B. Kazemian and L. Meng, "An adaptive control for video transmission over bluetooth," IEEE Trans. Fuzzy Syst., vol. 14, no. 2, pp. 263-274, Apr. 2006.
13. F.-J. Lin and P.-H. Shen, "Adaptive fuzzy-neural-network control for a DSP-based permanent magnet linear synchronous motor servo drive," IEEE Trans. Fuzzy Syst., vol. 14, no. 4, pp. 481-495, Aug. 2006.
14. A. Rubaai, A. R. Ofoli, L. Burge, and M. Garuba, "Hardware implementation of an adaptive network-based fuzzy controller for DC-DC converters," IEEE Trans. Ind. Appl., vol. 41, no. 6, pp. 1557-1565, Nov./Dec. 2005.
15. J. B. Theocharis, "A high-order recurrent neuro-fuzzy system with internal dynamics: Application to the adaptive noise cancellation," Fuzzy Sets Syst., vol. 157, no. 4, pp. 471-500, Feb. 2006.
16. R.-J. Wai and L.-J. Chang, "Stabilizing and tracking control of nonlinear dual-axis inverted-pendulum system using fuzzy neural network," IEEE Trans. Fuzzy Syst., vol. 14, no. 1, pp. 145-168, Feb. 2006.
17. M. E. Yüksel and E. Besdok, "A simple neuro-fuzzy impulse detector for efficient blur reduction of impulse noise removal operators for digital images," IEEE Trans. Fuzzy Syst., vol. 12, no. 6, pp. 854-865, Dec. 2004.
18. J. R. Jang, "ANFIS: Adaptive-network-based fuzzy inference system," IEEE Trans. Syst., Man, Cybern., vol. 23, no. 3, pp. 665-685, May 1993.
19. J.-S. R. Jang and C.-T. Sun, "Neuro-fuzzy modeling and control," Proc. IEEE, vol. 83, no. 3, pp. 378-406, Mar. 1995.
20. M. Sugeno and G. T. Kang, "Structure identification of fuzzy model," Fuzzy Sets Syst., vol. 28, no. 1, pp. 15-33, Oct. 1988.
21. T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. Syst., Man, Cybern., vol. SMC-15, no. 1, pp. 116-132, Jan. 1985.
22. D. Anguita, I. Baturone, and J. Miller, Eds., Appl. Soft Comput., vol. 4, 2004.
23. B. Linares-Barranco, A. G. Andreou, G. Indiveri, and T. Shibata, Eds., IEEE Trans. Neural Netw., vol. 14, no. 5, Sep. 2003, Special Issue on Neural Networks Hardware Implementation.
24. F. M. Salam and T. Yamakawa, Eds., Comput. Elect. Eng., vol. 25, 1999, Special Issue on Micro-Electronic Hardware Implementation of Soft Computing: Neural and Fuzzy Networks with Learning.
25. M. J. Patyra, Ed., IEEE Trans. Fuzzy Syst., vol. 4, no. 4, Nov. 1996, Special Issue on Fuzzy Logic Hardware Implementations.
26. Proc. IEEE, vol. 85, 1997, Special Issue on Hardware/Software Code-sign.
27. W. Wolf, Ed., "A decade of hardware/software codesign," Computer vol. 36, pp. 38-43, 2003.
28. L. M. Reyneri, "Implementation issues of neuro-fuzzy hardware: Going toward HW/SW codesign," IEEE Trans. Neural Netw., vol. 14, no. 1, pp. 176-194, Jan. 2003.
29. Datasheet of Excalibur Device, Altera Corporation. Online. Available: http://www.altera.com
30. I. Baturone, S. Sńchez-Solano, A. Barriga, and J. L. Huertas, "Design issues for the VLSI implementation of universal approximator fuzzy systems," in Proc. World MultiConf. Circuits, Systems, Communications, Computers, Athens, Greece, 1999, pp. 6471-6476.
31. I. Baturone, A. Barriga, S. Sńchez-Solano, C. J. Jiménez-Fernández, and D. R. López, Microelectronic Design of Fuzzy Logic-Based Systems. Boca Raton, FL: CRC, 2000.
32. J. Echanobe, I. del Campo, and J. M. Tarela, "Issues concerning the analysis and implementation of a class of fuzzy controllers," Fuzzy Sets Syst., vol. 155, no. 2, pp. 252-271, Oct. 2005.
33. R. Rovatti, C. Fantuzzi, and S. Simani, "High-speed DSP-based implementation of piecewise-affine and piecewise-quadratic fuzzy systems," Signal Process., vol. 80, no. 6, pp. 951-963, Jun. 2000.
34. I. Baturone, A. Barriga, S. Sánchez-Solano, and J. L. Huertas, "Mixed-signal design of a fully parallel fuzzy processor," Electron. Lett., vol. 34, no. 5, pp. 437-438, Mar. 1998.
35. J. Matas, L. G. deVicuña, and M. Castilla, "Asynthesis of fuzzy control surfaces in CMOS technology," in Proc. IEEE Int. Conf. Fuzzy Systems, Barcelona, Spain, 1997, pp. 641-646.
36. F. Vidal-Verdú, R. Navas-González, and A. Rodríguez-Vázquez, "Multiplexing architecture for mixed-signal CMOS fuzzy controllers," Electron. Lett., vol. 34, no. 14, pp. 1437-1439, Jul. 1998.
37. J.-S. R. Jang, C.-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing. Upper Saddle River, NJ: Prentice-Hall, 1997, ch. 8, pt. III.
38. S.-J. Lee and C.-S. Ouyang, "Aneuro-fuzzy system modeling with selfconstructing rule generation and hybrid SVD-based learning," IEEE Trans. Fuzzy Syst., vol. 11, no. 3, pp. 341-353, Jun. 2003.
39. Y. H. Lin, G. A. Cunningham, and S. V. Coggeshall, "Using fuzzy partitions to create fuzzy systems from input-output data and set the initial weights in a fuzzy neural network," IEEE Trans. Fuzzy Syst. vol. 5, no. 4, pp. 614-621, Nov. 1997.
40. C.-C.Wong and C.-C. Chen, "A hybrid clustering and gradient descent approach for fuzzy modeling," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 29, no. 12, pp. 686-693, Dec. 1999.
41. K. Basterretxea, J. M. Tarela, I. del Campo, and G. Bosque, "An experimental study on nonlinear function computation for neural/fuzzy hardware design," IEEE Trans. Neural Netw., vol. 18, no. 1, pp. 266-283, Jan. 2007.
42. J. Wray and G. G. Green, "Neural networks, approximation theory, and finite precision computation," Neural Netw., vol. 8, no. 1, pp. 31-37, 1995.
43. I. del Campo and J. M. Tarela, "Consequences of the discretization on the performance of a fuzzy logic controller," IEEE Trans. Fuzzy Syst., vol. 7, no. 1, pp. 85-92, Feb. 1999.
44. L. M. Reyneri and F. Renga, "Speeding-up the design of HW/SW implementations of neuro-fuzzy systems using the codesimulink environment," Appl. Soft. Comput., vol. 4, no. 3, pp. 227-240, Aug. 2004.
45. EPXA1 Development Board. Hardware Reference Manual, Altera Corporation, Online. Available: http://www.altera.com
46. Excalibur Solutions-Using the Embedded Stripe Bridges, Altera Corporation, Appl. Note 142.
47. K. Ducatel, M. Bogdanowicz, F. Scapolo, J. Leijten, and J.-C. Burgelman, "Scenarios for ambient intelligence in 2010," Tech. Rep., IST Advisory Group (ISTAG), Institutional Prospective Technology Studies (IPTS), 2001.
48. F. Doctor, H. Hagras, and V. Callaghan, "A fuzzy embedded agent-based approach for realizing ambient intelligence in intelligent inhabited environments," IEEE Trans. Syst., Man, Cybern. A, Syst. Humans, vol. 35, no. 1, pp. 55-65, Jan. 2005.