...Obaid Ur Rehman; Abid Saeed; Sadaqat Ur Rehman; Shafiullah Ullah Khan Purpose This study aims to investigate the effectiveness of quantum particle swarm optimization ( QPSO ) algorithms in solving electromagnetic optimization problems. Design/methodology/approach An enhanced version...

.... Design/methodology/approach A novel hybrid PLL method is proposed, combining particle swarm optimization (PSO) and gradient descent (GD) algorithms. The adaptive model continuously tunes PLL parameters, enabling real-time responsiveness to grid fluctuations, including voltage sags, phase shifts...

..., Leonardo Sandrolini and Mattia Simonazzi. 2024 Sami Barmada, Nunzia Fontana, Leonardo Sandrolini and Mattia Simonazzi. Licensed re-use rights only Particle swarm optimization Metamaterials Equivalent circuit model This paper investigates different approximations in the modelling...

... machine Pareto optimization Particle swarm optimization Magnetic device r, r₁, r₂, r₃, r₄, r₅, r and, y = Random values in the range [0 1]; GX...

... analytical approach. Subsequently, a genetic algorithm, the differential evolution algorithm and particle swarm optimization are tested and compared. The algorithms use the weighted mean squared error (MSE) between the real measured data of stator currents as well as speed and the simulation results...

...Javad Rahmani Fard; Saadat Jamali Arand; Siroos Hemmati Purpose In this paper, an improved multiobjective particle swarm optimization (PSO) algorithm is proposed to optimize a three-phase, 12-slot, 19-pole, yokeless axial-field flux-switching permanent magnet (YASA-AFFSPM) motor. Design...

... that the model output is in good agreement with the response of the real piezoelectric platform. Compared with the standard WOA and particle swarm optimization algorithms, the search performance of the proposed IWOA is better than those two competitors in terms of convergence speed and identification accuracy...

... using particle swarm optimization method on the created small signal-based simulation model of the system to minimize the integral time absolute error. To prove the success of the proposed method, a traditional fractional order proportional integral (TFOPI) controller is tested under the same...

... statistical outcomes are more aligned with the real-time experimental findings. Design/methodology/approach A novel metaheuristic efficient hybrid algorithm, i.e. hybrid particle swarm optimization rat search algorithm, is introduced and applied for parameter extraction of hybrid energy system...

... flow model has been developed for the optimal power flow (OPF) problem for VSC-based high voltage direct current (VSC-HVDC) transmission network and solved using a particle swarm optimization (PSO) algorithm. The impact of the HVDC converter under abnormal conditions considering N-1 line outage...

... algorithm (Singh and Singh, 2015), revised analytical hierarchy process (Sadanandan Sajan et al., 2016), the exponential binary particle swarm optimization) (Maji and Acharjee, 2017), ILP methodology (Pal et al., 2016) and binary cuckoo search (Babu et al., 2018...

...) : (9) γ ^ = H + T 10 07 2020 09 10 2020 03 12 2020 09 12 2020 © Emerald Publishing Limited 2021 Emerald Publishing Limited Licensed re-use rights only Optimal design Particle swarm optimization Forecasting Learning algorithm Meta-ELM Neural...

... = V L + I L R s R s h Optimal design Numerical analysis Fault analysis Particle swarm optimization Now, output current in equation (1) can be rewritten as follows: (4) I L = I p h − I S D [ exp ⁡ ( q ( V L + I L...

...Mohammad Amin Jarrahi; Emad Roshandel; Mehdi Allahbakhshi; Mohammad Ahmadi Purpose This paper aims to achieve an optimal design for distribution transformers considering cost and power losses. Particle swarm optimization (PSO) algorithm is used as an optimization tool for minimizing the objective...

... compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were...

..., a particle swarm optimization (PSO) method (Huynh and Dunnigan, 2010 ; Karimi et al., 2007 ; Kennedy and Eberhart, 1995); second, an R-X method (Lin et al., 2012), which relies on the measured overall machine reactance and resistance; and third, an evolutionary strategy (Rechenberg, 1984...

...Bourahla Kheireddine; Belli Zoubida; Hacib Tarik; Achoui Imed Purpose This study aims to focus on the application of the stochastic algorithms for optimal design of electrical machines. Among them, the authors are interested in particle swarm optimization and teaching–learning-based optimization...

...Shafiullah Khan; Shiyou Yang; Obaid Ur Rehman Purpose The aim of this paper is to explore the potential of particle swarm optimization (PSO) algorithm to solve an electromagnetic inverse problem. Design/methodology/approach A modified PSO algorithm is designed. Findings The modified PSO...

... 2017 15 08 2017 17 08 2017 © Emerald Publishing Limited 2018 Emerald Publishing Limited Licensed re-use rights only Multi-objective optimization Particle swarm optimization Distributed generation Plant propagation algorithm Real losses Weighting factor (2) Q k...

...Obaid Ur Rehman; Shiyou Yang; Shafi Ullah Khan Purpose The purpose of this paper is to explore the potential of standard quantum-based particle swarm optimization (QPSO) methods for solving electromagnetic inverse problems. Design/methodology/approach A modified QPSO algorithm is designed...