Abstract
Fuzzy systems play an important role in many industrial applications. Depending on the application, they can be implemented using different techniques and technologies. Software implementations are the most popular, which results from the ease of such implementations. This approach facilitates modifications and testing. On the other hand, such realizations are usually not convenient when high data rate, low cost per unit, and large miniaturization are required. For this reason, we propose efficient, fully digital, parallel, and asynchronous (clock-less) fuzzy logic (FL) systems suitable for the implementation as ultra low-power-specific integrated circuits (ASICs). On the basis of our former work, in which single FL operators were proposed, here we demonstrate how to build larger structures, composed of many operators of this type. As an example, we consider Lukasiewicz neural networks (LNN) that are fully composed of selected FL operators. In this work, we propose FL OR, and AND Lukasiewicz neurons, which are based on bounded sum and bounded product FL operators. In the comparison with former analog implementations of such LNNs, digital realization, presented in this work, offers important advantages. The neurons have been designed in the CMOS 130nm technology and thoroughly verified by means of the corner analysis in the HSpice environment. The only observed influence of particular combinations on the process, voltage, and temperature parameters was on delays and power dissipation, while from the logical point of view, the system always worked properly. This shows that even larger FL systems may be implemented in this way.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Tan, Q., Wei, Q., Hu, J., Aldred, D.: Road vehicle detection using fuzzy logic rule-based method. In: International Conference on Fuzzy Systems and Knowledge Discovery, pp. 3 (2010)
Sharma, K., Kumar Palwalia, P.: A modified PID control with adaptive fuzzy controller applied to DC motor. In: International Conference on Information, Communication, Instrumentation and Control (ICICIC) (2017)
Chen, Z., Gomez, S.A., McCormick, M.: A fuzzy logic controlled power electronic system for variable speed wind energy conversion systems. In: International Conference on Power Electronics and Variable Speed Drives (2000)
Sreedivya, K.M., Aruna Jeyanthy, P., Devaraj, D.: Fuzzy logic based power system stabilizer for damping low frequency oscillations in power system. In: International Conference on Innovations in Electrical, Electronics, Instrumentation and Media Technology (ICEEIMT) (2017)
Seker, H., Odetayo, M.O., Petrovic, D., Naguib, R.N.G.: A fuzzy logic based-method for prognostic decision making in breast and prostate cancers. IEEE Trans. Inf. Technol. Biomed. 7, 2 (2003)
Cetin, O., Kurnaz, S., Kaynak, O.: Fuzzy logic based approach to design of autonomous landing system for unmanned aerial vehicles. J. Intell. Robot. Syst. 61, 239–250 (2011)
Jin, M., Zhao J., Jin J., Yu G., Li W.: The adaptive Kalman filter based on fuzzy logic for inertial motion capture system. Measurement, Elsevier 7, 196–204 (2014)
Banach, M., Wasilewska, A., Długosz, R., Pauk, J.: Novel techniques for a wireless motion capture system for the monitoring and rehabilitation of disabled persons for application in smart buildings. Technol. Health Care, IOS Press 26(S2), 671–677 (2018)
Milanés, V., Villagrá, J., Godoy, J., Simó, J., Pérez, J., Onieva, E.: An intelligent V2I-Based traffic management system. IEEE Trans. Intell. Transp. Syst. 1(49-58), 13 (2012)
Salman, M.A., Ozdemir S., Celebi F.V.: Fuzzy traffic control with vehicle-to-everything communication, Sensors, https://doi.org/10.3390/s1802036827, (368) (2018)
Banach, M., Długosz, R.: Real-time locating systems for smart city and intelligent transportation applications. In: IEEE 30th International Conference on Microelectronics (Miel 2017) (231-234) (2017)
Li, T.H.S., Chen, Ch.-Y., lim, K.-CH.: Combination of fuzzy logic control and back propagation neural networks for the autonomous driving control of car-like mobile robot systems. In: Proceedings of SICE Annual Conference (2010)
Kayacan, E., Kayacan, E.L., Ramon, H., Saeys, W.: Adaptive Neuro-Fuzzy control of a spherical rolling robot using Sliding-Mode-Control-Theory-Based online learning algorithm. IEEE Transactions on Cybernetics 43, 1 (2013)
Allah Hooshmand, R., Parastegari, M., Forghani, Z.: Adaptive neuro-fuzzy inference system approach for simultaneous diagnosis of the type and location of faults in power transformers. IEEE Electr. Insul. Mag. 28, 5 (2012)
Yen, J., Langari, R., Zadeh, L.A.: Industrial Applications of Fuzzy Logic and Intelligent Systems. IEEE Press, New York (1995)
Nagaraj, R., Mayurappriyan, P.S., Jerome, J.: Microcontroller based fuzzy logic technique for dc-dc converter. In: International Conference on Power Electronics (2006)
Rudas, I.J., Batyrshin, I.Z., Hernández Zavala, A., Camacho Nieto, O., Horváth, L., Villa Vargas, L.: Generators of fuzzy operations for hardware implementation of fuzzy systems, advances in artificial intelligence. In: 7th Mexican International Conference on Artificial Intelligence (MICAI) (2008)
Meisam Ramzanzad. M., Rashidy Kanan, H.: A new method for design and implementation of intelligent traffic control system based on fuzzy logic using FPGA. In: Iranian Conference on Fuzzy Systems (IFSC) (2013)
Guo, S., Peters, L., Surmann, H.: Design and application of an analog fuzzy logic controller. IEEE Trans. Fuzzy Syst. 4, 4 (1996)
Yamakawa, T., Miki, T.: The current mode fuzzy logic integrated circuits fabricated by the standard CMOS process. IEEE Trans. Comput. C-35, 2 (1986)
Długosz, R., Pedrycz, W.: Łukasiewicz fuzzy logic networks and their ultra low power hardware implementation, Neurocomputing, Elsevier, 73 (2010)
Sanchez-Solano, S., Barriga, A., Jimenez, C.J., Huertas, J.L.: Design and application of digital fuzzy controllers. In: International Fuzzy Systems Conference (1997)
Baturone, I., Sanchez-Solano, S., Barriga, A., Huertas, J.: Implementation of CMOS fuzzy controllers as Mixed-Signal integrated circuits. IEEE Trans. Fuzzy Syst. 5, 1 (1997)
Talaśka, T., Długosz, R., Skruch, P.: Efficient transistor level implementation of selected fuzzy logic operators used in control systems. In: Advances in Intelligent Systems and Computing, Trends in Advanced Intelligent Control, Optimization and Automation, vol. 577. Springer (2017)
Talaśka, T.: Implementation of fuzzy logic operators as digital asynchronous circuits in CMOS technology. In: International Conference on Microelectronics (MIEL) (2017)
Navi, K., Doostaregan, A., Moaiyeri, M., Hashemipour, O.: A hardware-friendly arithmetic method and efficient implementations for designing digital fuzzy adders. Fuzzy Set. Syst, Elsevier 185(1), 111–124 (2011)
Zavala, A.H., Batyrshin, L.Z., Nieto, O.C., Castillo, O.: Conjunction and disjunction operations for digital fuzzy hardware. Appl. Soft. Comput. 13, 7 (2013)
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by: Pavel Solin
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
OpenAccess This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Talaśka, T. Parallel, asynchronous, fuzzy logic systems realized in CMOS technology. Adv Comput Math 45, 1807–1823 (2019). https://doi.org/10.1007/s10444-018-09659-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10444-018-09659-5
Keywords
- Fuzzy logic systems
- FL operators
- FL neural networks
- Asynchronous circuits
- Parallel circuits
- CMOS implementation