Comparative Analysis Between Two Fuzzy Variants of Harmonic Search Algorithm: Fuzzy Fault Tolerant Control Application

Abstract

The goal of this research is to improve the harmonic search (HS) algorithm by using type-1 and interval type-2 fuzzy systems to dynamically change one of the evolutionary method's parameters. We have previously used both sorts of fuzzy systems in a variety of benchmark challenges and discovered that using fuzzy logic in conjunction with the harmonic search algorithm produces good results. In some of the experiments, it is clearly demonstrated that our methodology is statistically superior to other algorithms. Using type-1 and interval type-2 fuzzy systems, the harmony memory (HMR) parameter is dynamically changed during the evolution process in this example. The fundamental contribution of this work is the capacity to establish, by experimentation in a benchmark control issue, which of the two types of fuzzy systems employed with the harmonic search method produces better results. This is because there are no previous studies to our idea that employ and compare type-1 and interval type-2 fuzzy systems. Furthermore, three type of uncertainties are employed in the benchmark two-tank level control system to assess the performance of both fuzzy systems, simulating the disturbances that may present in the actual world and therefore allowing statistical validation if there are substantial differences between type-1 and interval type-2 fuzzy systems.