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User-Selected Sets of Algorithmic Implementation of Fuzzy Processing Subsystem for Embedded Intelligent Control Systems

Year 2023, Volume: 24, 257 - 262, 30.11.2023

Alexei Evgenievich Vassiliev Htut Shine Ye Min Htet Viktoriia Alexeevna Karpenko

https://doi.org/10.55549/epstem.1406787

Abstract

Embedded intelligent control systems (EICS) have been used in a wide range of tasks involving the adaptive control of technical objects and processes. For the hardware implementation of EICS, developers actively use function-oriented microcontrollers, that aimed to be the effective implementation of control algorithms, including adaptive and intelligent control. Embedded control systems based on the concept of fuzzy set theory have recently been developed for specific individual control operations, allowing more efficient implementation of complex object control algorithms. This paper approaches the study of the different implementation of control algorithms in embedded microcontrollers based on fuzzy sets theory to result in reduced hardware area and complexity, high operating speed, and adaptability to various applicable domains. It shows that the performance of fuzzy computing specialized in embedded systems has significantly increased and makes possible a huge scope for further improvement of the implementation of fuzzy control algorithms at the hardware level.

Keywords

: Embedded control system MCS-51 Control algorithms Fuzzy sets Fuzzy computation

References

  • Ascia, G., Catania, V., & Russo, M. (1999). VLSI hardware architecture for complex fuzzy systems. IEEE Transactions on Fuzzy Systems, 7(5), 553–570.
  • Barrett, S. F., & Magleby, D. B. (2004). Embedded systems: Design and applications with the 68HC12 and HCS12. Retrieved from https://www.amazon.com/Embedded-Systems-Design-Applications.
  • Evmorfopoulos, N., & Avaritsiotis, J. (2002). An adaptive digital fuzzy architecture for application-specific integrated circuits. Active and Passive Electronic Components,25(4), 289-306.

Year 2023, Volume: 24, 257 - 262, 30.11.2023

Alexei Evgenievich Vassiliev Htut Shine Ye Min Htet Viktoriia Alexeevna Karpenko

https://doi.org/10.55549/epstem.1406787

Abstract

References

  • Ascia, G., Catania, V., & Russo, M. (1999). VLSI hardware architecture for complex fuzzy systems. IEEE Transactions on Fuzzy Systems, 7(5), 553–570.
  • Barrett, S. F., & Magleby, D. B. (2004). Embedded systems: Design and applications with the 68HC12 and HCS12. Retrieved from https://www.amazon.com/Embedded-Systems-Design-Applications.
  • Evmorfopoulos, N., & Avaritsiotis, J. (2002). An adaptive digital fuzzy architecture for application-specific integrated circuits. Active and Passive Electronic Components,25(4), 289-306.
There are 3 citations in total.

Details

Primary Language English
Subjects Control Theoryand Applications
Journal Section Articles
Authors

Alexei Evgenievich Vassiliev

Htut Shine

Ye Min Htet

Viktoriia Alexeevna Karpenko

Early Pub Date December 19, 2023
Publication Date November 30, 2023
Published in Issue Year 2023 Volume: 24

Cite

APA Vassiliev, A. E., Shine, H., Htet, Y. M., Karpenko, V. A. (2023). User-Selected Sets of Algorithmic Implementation of Fuzzy Processing Subsystem for Embedded Intelligent Control Systems. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 24, 257-262. https://doi.org/10.55549/epstem.1406787
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