Unit Commitment Solution Based on Improved Particle Swarm Optimization Method

Abbas, Ali; Anwer, Afaneen

doi:10.30684/etj.v39i10.2114

Cited by 1 publication

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, Pbest refers to the place with the best fitness, whereas gbest refers to the overall best of the population's particles. In this work [13], PSO was utilized for tuning the weight coefficients in order to obtain an optimal controller. In PSO, a swarm of randomly selected individuals referred to as particles is produced.…”

Section: Pi Speed Controllersmentioning

confidence: 99%

“…where, the above equation's parameters have been specified in advance and ω represents the weight factor of the inertia, which has been characterized as [13]:…”

Section: Pi Speed Controllersmentioning

confidence: 99%

“…Omega wolves use alpha, beta, and delta sites to update their sites. The first ideal solution is alpha, while 2 nd and 3 rd ideal solutions are respectively (beta) and (delta) [7][8][9][10][11][12][13][14][15][16].…”

Section: Grey Wolf Optimization (Gwo)mentioning

confidence: 99%

See 2 more Smart Citations

Design a PI Controller Based on PSO and GWO for a Brushless DC Motor

Abedulabbas¹,

Yaseen²

2022

JESA

View full text Add to dashboard Cite

Recently all the moving mechanical parts that are subjected to wear and cause errors in the future are replaced with the equivalent of electrical. A Brushless Direct Current (BLDC) motor is preferable compared to a brushed DC motor because it substitutes the unit of mechanical commutations with an electronic unit, enhancing dynamic properties, noise level, and efficiency. Since it is fairly inexpensive, simple in structure, and performs well, maximum BLDC motor drives use a Proportional-Integral PI controller for controlling the machine's speed. The major issue with the PI controller, on the other hand, is altering its parameters throughout the deployment. As a result, this work shows how to tune the PI controller settings of a BLDC motor drive using Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). The results of a comparison of PSO and GWO for BLDC motors were obtained. Simulation tests for the BLDC engine in MATLAB/Simulink environment show that both PSO and GWO of BLDC motor give good results, but the best is GWO in tested in terms of transient response under different mechanical loads and speeds.

show abstract

Section: Pi Speed Controllersmentioning

confidence: 99%

“…where, the above equation's parameters have been specified in advance and ω represents the weight factor of the inertia, which has been characterized as [13]:…”

Section: Pi Speed Controllersmentioning

confidence: 99%