Particle Swarm Optimization (PSO) Projects

PSO Particle Swarm Optimization Projects

AT-PSO-1An Improved Current-Limiting Strategy for Shunt Active Power Filter (SAPF) Using Particle Swarm Optimization (PSO)
AT-PSO-2Improved Dynamic Performance of Shunt Active Power Filter Using Particle Swarm OptimizationDownload
AT-PSO-3Particle Swarm Optimization Based Shunt Active Harmonic Filter for Harmonic CompensationDownload
AT-PSO-4PI tuning of Shunt Active Filter using GA and PSO Algorithm
AT-PSO-5PSO - PI Based DC Link Voltage Control Technique for Shunt Hybrid Active Power FilterDownload

The table lists the latest Particle Swarm Optimization  PSO Projects-

A particle swarm searching for the global minimum of a function

In computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solutionwith regard to a given measure of quality. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle’s position and velocity. Each particle’s movement is influenced by its local best known position, but is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expected to move the swarm toward the best solutions.