scholarly journals Multiobjective Optimization of Switched Reluctance Motors Based on Design of Experiments and Particle Swarm Optimization

2015 ◽  
Vol 30 (3) ◽  
pp. 1144-1153 ◽  
Author(s):  
Cong Ma ◽  
Liyan Qu
Keyword(s):  
Particle Swarm Optimization ◽  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Particle Swarm ◽  
Switched Reluctance Motors ◽  
Swarm Optimization ◽  
Switched Reluctance

scholarly journals Research on Multiaircraft Cooperative Suppression Interference Array Based on an Improved Multiobjective Particle Swarm Optimization Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Huan Zhang ◽  
Rennong Yang ◽  
Changyue Sun ◽  
Haiyan Han
Keyword(s):  
Particle Swarm Optimization ◽  
Multiobjective Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Minimum Width ◽  
Air Defense ◽  
Radar Network ◽  
Multiobjective Particle Swarm Optimization

For the problem of multiaircraft cooperative suppression interference array (MACSIA) against the enemy air defense radar network in electronic warfare mission planning, firstly, the concept of route planning security zone is proposed and the solution to get the minimum width of security zone based on mathematical morphology is put forward. Secondly, the minimum width of security zone and the sum of the distance between each jamming aircraft and the center of radar network are regarded as objective function, and the multiobjective optimization model of MACSIA is built, and then an improved multiobjective particle swarm optimization algorithm is used to solve the model. The decomposition mechanism is adopted and the proportional distribution is used to maintain diversity of the new found nondominated solutions. Finally, the Pareto optimal solutions are analyzed by simulation, and the optimal MACSIA schemes of each jamming aircraft suppression against the enemy air defense radar network are obtained and verify that the built multiobjective optimization model is corrected. It also shows that the improved multiobjective particle swarm optimization algorithm for solving the problem of MACSIA is feasible and effective.

Particle Swarm Optimization Method to Design a Linear Tubular Switched Reluctance Generator

2015 ◽  
pp. 469-506
Author(s):  
Rui P. G. Mendes ◽  
Maria do Rosário Alves Calado ◽  
Sílvio José Mariano
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Optimization Method ◽  
Relative Displacement ◽  
Rate Of Change ◽  
Swarm Optimization ◽  
Switched Reluctance ◽  
Electric Generation ◽  
Particle Swarm Optimization Method ◽  
Structural Configurations

In this chapter, the Particle Swarm Optimization method is applied to four different structural configurations of a linear switched reluctance generator with tubular topology. The optimization process involves the search of the values for a defined set of geometric parameters that maximize the rate of change of the generator's inductance with the relative displacement of its mover part. The optimization algorithm is applied to each structural configuration in order to find the optimum geometry as well to identify the most suitable configuration for electric generation.

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