he Interval Type-2 Fuzzy Logic Control (IT2FLC) utilizes a genetic algorithm (GA), known as the Genetics Interval Type-2 Fuzzy Network (GIT2FS), to optimize the fuzzy parameters, including fuzzy functions for membership andfuzzy regulation bases. After a brief discussion of the genetic fuzzy system GFS, the suggested design is described.Type reductions and defuzzification are included in the output processing of intervaltype-2 fuzzy logic circuits. Although researchers have recently developed numerous effective type reduction techniques, there are currently no practical plans to enhancethe output of defuzzification. The kind of interval type-2 fuzzy set is reduced using the type reduction algorithm presented in this paper, which also produces the best defuzzified output from the type-reduced set. Theplanned type reduction is also carried out offline (in other words, the controller has been reduced to type-1 in practical applications).It greatly lowers the computational expense and makes it easier,actually, to develop controllers. Problems with truck backing control are used to show the viability of the suggested approach. The study showed that,in terms of speed, computational complexity, and resilience, the suggested technique performs better than typical IT2-FLCs.
Jinan Redha Mutar (Wed,) studied this question.