TY  - JOUR
T1  - User-Selected Sets of Algorithmic Implementation of Fuzzy Processing Subsystem for Embedded Intelligent Control Systems
AU  - Vassiliev, Alexei Evgenievich
AU  - Shine, Htut
AU  - Htet, Ye Min
AU  - Karpenko, Viktoriia Alexeevna
PY  - 2023
DA  - November
DO  - 10.55549/epstem.1406787
JF  - The Eurasia Proceedings of Science Technology Engineering and Mathematics
JO  - EPSTEM
PB  - ISRES Publishing
WT  - DergiPark
SN  - 2602-3199
SP  - 257
EP  - 262
VL  - 24
LA  - en
AB  - 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.
KW  - : Embedded control system
KW  - MCS-51
KW  - Control algorithms
KW  - Fuzzy sets
KW  - Fuzzy computation
CR  - Ascia, G., Catania, V., & Russo, M. (1999). VLSI hardware architecture for complex fuzzy systems. IEEE Transactions on Fuzzy Systems, 7(5), 553–570.
CR  - 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.
CR  - Evmorfopoulos, N., & Avaritsiotis, J. (2002). An adaptive digital fuzzy architecture for application-specific integrated circuits. Active and Passive Electronic Components,25(4), 289-306.
UR  - https://doi.org/10.55549/epstem.1406787
L1  - https://dergipark.org.tr/en/download/article-file/3607625
ER  -