A Novel Bio-Inspired Algorithm Applied to Selective Harmonic Elimination in a Three-Phase Eleven-Level Inverter

Abstract

Selective harmonics elimination (SHE) is a widely applied control strategy in multilvel inverters for harmonics reduction. SHE is designed for the elimination of low-order harmonics while keeping the fundamental component equal to any previously specified amplitude. This paper proposes a novel bio-inspired metaheuristic optimization algorithm called Black Widow Optimization Algorithm (BWOA) for solving the SHE set of equations. BWOA mimics the spiders’ different movement strategies for courtship-mating, guaranteeing the exploration and exploitation of the search space. The optimization results show the reliability of BWOA compared to the state-of-the-art metaheuristic algorithms and show competitive results as a microalgorithm, opening its future application for an on-line optimization calculation in low requirement hardware.

Internet of Things and Synergic Deep Learning Based Biomedical Tongue Color Image Analysis for Disease Diagnosis and Classification

“…Males, utilize sex pheromone to distinguish female mating position, are well-known to demonstrate no concern in mating with poorly and starving fed females, since females could exhibit cannibalistic performance. More detail regarding black widow spider's performance is made in [30]. Fig.…”

A Bio-Inspired Method for Mathematical Optimization Inspired by Arachnida Salticidade

“…Whereas, in the Jumping spider the courtship-mating is based on its striking colors. Nevertheless, they also produce pheromones; the modeling of the rate of pheromones is taken from [15] and defined in the following equation:…”

“…Many metaheuristics have been developed in recent years; they can be classified into the following categories: Swarm-Based Algorithms, which include Particle Swarm Optimization (PSO) [8], Salp Swarm Algorithm (SSA) [9], Whale Optimization Algorithm (WOA) [10], Chameleon Swarm Algorithm (CSA) [11], Orca Predation Algorithm (OPA) [12], African Vultures Optimization Algorithm (AVOA) [13], Dingo Optimization Algorithm (DOA) [14], Black widow Optimization Algorithm (BWOA) [15], Coot Bird Algorithm (COOT) [16], Mexican Axolotl Optimization (MAO) [17], Golden Eagle Optimizer (GEO) [18], Ant Lion Optimizer (ALO) [19], Coronavirus Optimization (CRO) [20], Archimedes Optimization algorithm (AOA) [21], Arithmetic Optimization Algorithm (ArOA) [22], Gradient-base Optimizer (GBO) [23], Hunger Game Search (HGS) [24], Henry Gas Solubility Optimization (HGSO) [25], Harris Hawks Optimization (HHO) [26], among others.…”

A Bio-Inspired Method for Engineering Design Optimization Inspired by Dingoes Hunting Strategies

“…erefore, designing new optimization techniques is an active research field within the scientific community [17]. A survey of some of the most relevant animal or natured based bio-inspired algorithms includes but is not limited to Virus Colony Search (VCS) [18], Plant Propagation algorithms [19], Lightning Search Algorithm (LSA) [20], Ant Lion Optimizer (ALO) [21], Lion Optimizer Algorithm (LOA) [22], Spotted Hyena Optimizer (SHO) [23], Harris Hawks Optimization (HHO) [24], Dragonfly Algorithm (DFA) [25], Grey Wolf Optimizer (GWO) [26], Dolphin Echolocation Algorithm [27], Water Strider Algorithm (WSA), [27], Slime Mould Algorithm (SMA) [28], Moth Search Algorithm (MSA) [29], Colony Predation Algorithm (CPA) [30], Black Widow Optimization Algorithm (BWOA) [31], Grasshopper Optimization Algorithm (Goa) [32], and the Hunger games search (HGS) [33]. Additionally, some outstanding physical phenomena based bio-inspired algorithm for optimization are [27]: Magnetic Charged System Search (MCSS), Colliding Bodies Optimization (CBO), Water Evaporation Optimization (WEO), Vibrating Particles System (VPS), ermal Exchange Optimization (TEO), Cyclical Parthenogenesis Algorithm (CPA), among others.…”