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

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.