A comprehensive survey on particle swarm optimization algorithm and its applications
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
Online parameter estimation for permanent magnet synchronous machines: An overview
Online parameter estimation of permanent magnet synchronous machines is critical for
improving their control performance and operational reliability. This paper provides an …
improving their control performance and operational reliability. This paper provides an …
Genetic learning particle swarm optimization
Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas
individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This …
individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This …
A survey on cooperative co-evolutionary algorithms
The first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong
in 1994 and since then many CCEAs have been proposed and successfully applied to …
in 1994 and since then many CCEAs have been proposed and successfully applied to …
Phasor particle swarm optimization: a simple and efficient variant of PSO
Particle swarm optimizer is a well-known efficient population and control parameter-based
algorithm for global optimization of different problems. This paper focuses on a new and …
algorithm for global optimization of different problems. This paper focuses on a new and …
General formulation of Kalman-filter-based online parameter identification methods for VSI-fed PMSM
X Li, R Kennel - IEEE Transactions on Industrial Electronics, 2020 - ieeexplore.ieee.org
This article proposes two Kalman-filter-based online identification schemes for permanent
magnet synchronous machines (PMSMs), where the nonlinearity of a voltage-source …
magnet synchronous machines (PMSMs), where the nonlinearity of a voltage-source …
TTSA: An effective scheduling approach for delay bounded tasks in hybrid clouds
The economy of scale provided by cloud attracts a growing number of organizations and
industrial companies to deploy their applications in cloud data centers (CDCs) and to …
industrial companies to deploy their applications in cloud data centers (CDCs) and to …
Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO
A global parameter estimation method for a permanent magnet synchronous machines
(PMSM) drive system is proposed, where the electrical parameters, mechanical parameters …
(PMSM) drive system is proposed, where the electrical parameters, mechanical parameters …
Composite particle swarm optimizer with historical memory for function optimization
J Li, JQ Zhang, CJ Jiang… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Particle swarm optimization (PSO) algorithm is a population-based stochastic optimization
technique. It is characterized by the collaborative search in which each particle is attracted …
technique. It is characterized by the collaborative search in which each particle is attracted …
Parameter estimation for VSI-fed PMSM based on a dynamic PSO with learning strategies
A dynamic particle swarm optimization with learning strategy (DPSO-LS) is proposed for key
parameter estimation for permanent magnet synchronous machines (PMSMs), where the …
parameter estimation for permanent magnet synchronous machines (PMSMs), where the …