Abstract
The design approaches & constraints for hardware implementation of fuzzy logic controllers are discussed here. The digital, analog & mixed analog domains are compared. Apart from these the Memory based approach & MFC based approach are discussed. Silicon area & operational speed are the major constraints for fuzzy controllers. Most hardware implementations of fuzzy controllers use piece-wise linear functions to represent membership functions. The existing analog approach for the design of fuzzy controllers offer parallel computing with lower hardware resources but they implement much lesser rules than the fully digital ones. Compared to its analog counterpart, the digital approach has greater flexibility, easier design automation, and good compatibility with other digital systems but they are more complex and need larger chip area. Analog approach can be faster & enough flexible to compete digital fuzzy approaches. Working with digital signal limits the application to low-speed problems due to sequential calculation of fuzzy logic quantities.
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References
Yamakawa: A fuzzy inference engine in non-linear analog mode and its application to a fuzzy logic control. IEEE Trans. on Neural Networks 4(3), 496–522 (1993)
Watanabe,, et al.: A VLSI fuzzy logic controller with reconfigurable, cascadable architecture. IEEE Journal of Solid State circuits 25(2), 376–382 (1990)
Lago, E., Hinojosa, M.A., Jiménez, C.J., Barriga, A., Sánchez-Solano, S.: FPGA Implementation Of Fuzzy Controllers. In: XII Conference on Design of Circuits and Integrated Systems (DCIS 1997), Sevilla, November 18-21, pp. 715–720 (1997)
Jiménez, C.J., Sánchez Solano, S., Barriga, A.: Hardware Implementation Of A General Purpose Fuzzy Controller. In: Sixth International Fuzzy Systems Association World Congress (IFSA 1995), Sao Paulo - Brazil, July 21-28, vol. 2, pp. 185–188 (1995)
Barriga, A., et al.: Automatic Synthesis Of Fuzzy Logic Controller. Mathware & Soft Computing III(3), 425–434 (1996)
Guo, S., et al.: Design and Application of an Analog Fuzzy Logic Controller. IEEE Transactions on Fuzzy Systems 4(4), 429–438 (1996)
Galán, D., Jiménez, C.J., Barriga, A., Sánchez Solano, S.: VHDL Package For Description Of Fuzzy Logic Controllers. In: European Design Automation Conference (EURO-VHDL 1995), Brighton - Great Britain, September 18-22, pp. 528–533 (1995)
Blake, J.J., et al.: The Implementation of Fuzzy systems, Neural Networks & Fuzzy Neural Networks using FPGAs. Information Sciences 112, 151–168 (1998)
Baturone, I., Sánchez Solano, S., Barriga, A., Huertas, J.L.: Optimization Of Adaptive Fuzzy Processor Design. In: XIII Conference on Design of Circuits and Integrated Systems (DCIS 1998), Madrid, November 17-20, pp. 316–321 (1998)
Cotta, C., Alba, E., Troya, J.M.: Evolutionary Design Of Fuzzy Logic Controllers. In: XIII Conference on Design of Circuits and Integrated Systems (DCIS 1998), Madrid, November 17-20, pp. 316–321 (1998)
Madrenas, J., Alarcón, E., Cosp, J., Moreno, J.M., Poveda, A., Cabestany, J.: Mixed-Signal VLSI for Neural and Fuzzy Sequential Processors. In: Proceedings of the 2000 IEEE International Symposium on Circuits and Systems - ISCAS 2000, Geneva, Switzerland (June 2000)
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Deshmukh, A., Bajaj, P., Keskar, A.G. (2006). Hardware Implementation of Fuzzy Controllers-Approach and Constraints. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11892960_6
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DOI: https://doi.org/10.1007/11892960_6
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