2012
DOI: 10.1109/tmag.2012.2204764
|View full text |Cite
|
Sign up to set email alerts
|

Genetic Algorithm Approach for Improved Design of a Variable Speed Axial-Flux Permanent-Magnet Synchronous Generator

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
20
0
1

Year Published

2013
2013
2023
2023

Publication Types

Select...
9
1

Relationship

0
10

Authors

Journals

citations
Cited by 55 publications
(21 citation statements)
references
References 21 publications
0
20
0
1
Order By: Relevance
“…The minimal cost design of an axial flux permanent magnet generator was searched by using a genetic algorithm with consideration of practical and performance constraints. Improved design procedure of AFPM using GA is shown in Figure 3 [24].…”
Section: Analysis and Optimization Methodsmentioning
confidence: 99%
“…The minimal cost design of an axial flux permanent magnet generator was searched by using a genetic algorithm with consideration of practical and performance constraints. Improved design procedure of AFPM using GA is shown in Figure 3 [24].…”
Section: Analysis and Optimization Methodsmentioning
confidence: 99%
“…In 2012, further utilized genetic algorithm (GA) for the achievement of an optimal design for an axial-flux PMSG (AFPMSG) [96]. In 2009, [97] proposed an approach based on a numerical optimization algorithm wherein a generalized receding horizon control of fuzzy systems was proposed.…”
Section: Soft Computing Technique Based Optimization Used For Pmsgsmentioning
confidence: 99%
“…A proposal is done on the results obtained from GA using computer aided procedure. During the design procedure, consideration is done on the practical and performance characteristics due to the limitations for the object function in the optimization algorithm [201]. Chonghui Song, et al, (2009) based on numerical optimization algorithm, presented a generalized receding horizon control of fuzzy systems.…”
Section: Soft Computing Techniques-based Optimization Used Pmsgsmentioning
confidence: 99%