Grey wolf optimizer (GWO) is one of recent metaheuristics swarm intelligence methods. It
has been widely tailored for a wide variety of optimization problems due to its impressive …

Fuzzy control has long been applied to industry with several important theoretical results
and successful results. Originally introduced as model-free control design approach, model …

This study proposes a new nature-inspired metaheuristic that mimics the behaviour of the
prairie dogs in their natural habitat called the prairie dog optimization (PDO). The proposed …

This article presents a hybrid metaheuristic optimization algorithm that combines particle
filter (PF) and particle swarm optimization (PSO) algorithms. The new PF–PSO algorithm …

This paper presents a novel nature-inspired optimization paradigm, named as squirrel
search algorithm (SSA). This optimizer imitates the dynamic foraging behaviour of southern …

Meta-heuristic search algorithms were successfully used to solve a variety of problems in
engineering, science, business, and finance. Meta-heuristic algorithms share common …

With a hypothesis that the social hierarchy of the grey wolves would be also followed in their
searching positions, an improved grey wolf optimization (GWO) algorithm with variable …

This paper proposes an innovative tuning approach for fuzzy control systems (CSs) with a
reduced parametric sensitivity using the Grey Wolf Optimizer (GWO) algorithm. The CSs …

In this article, an optimal control strategy for a bearingless permanent magnet synchronous
machine (BPMSM) drive is proposed. The state feedback control (SFC) based on the grey …

The goal of this paper is to develop the optimal fuzzy controllers for nonlinear processed
represented by electromagnetic actuated clutch systems in order to improve the control …