A Fuzzy Variant of the Multi-verse Optimizer for Optimal Design of Fuzzy Controllers

Abstract

AbstractIn this work we propose a dynamic parameter adaptation approach using Fuzzy logic over the Multi-verse Optimizer algorithm (FMVO), which is tested with benchmark functions and control problems. For this study, we use some control problems, one is cruise control, which focuses on achieving a desired speed on a vehicle with a certain weight; from here, we use the temperature control in a shower, which controls the temperature of the water by adjusting the water valves, the last control problem is the inverted pendulum, which is one of the most common test control problems used for optimization in fuzzy logic controllers; all of these problems focus on optimizing membership functions for the fuzzy inference system using Mamdani and Sugeno models in the tests. The objective of this study is to determine if the Multi-verse Optimizer is improved by dynamically adjusting some of its parameters using fuzzy logic, making it more competitive over other metaheuristics.KeywordsMulti-verse optimizerMetaheuristicsControl problemsFuzzy logicStudyOptimizationDynamic parameterMamdaniSugenoFMVO