Abstract
The harmony search (HS) and differential evolution (DE) algorithms are compared in this study. Additionally, an interval type-2 fuzzy logic system (IT2FLS) allowing dynamic change of the key parameters is offered for each algorithm. The use of fuzzy systems to dynamically alter the primary parameters for each algorithm seeks to improve the performance of the associated algorithms. The optimal design of fuzzy systems for benchmark control issues, particularly in fuzzy controller design, is used to evaluate and compare each algorithm (IT2FHS and IT2FDE). Simulation results demonstrate that the FHS method outperforms the FDE approach when it comes to fuzzy controller optimization. The better errors are found with the application of fuzzy systems to enhance each proposed algorithm, according to statistics.
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