Design optimization of brushless DC motor using Particle Swarm Optimization

2014 ◽  
Author(s):  
N. Umadevi ◽  
M. Balaji ◽  
V. Kamaraj
Keyword(s):  
Particle Swarm Optimization ◽  
Design Optimization ◽  
Particle Swarm ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Swarm Optimization ◽  
Brushless Dc

scholarly journals PI Controller of Speed Regulation of Brushless DC Motor Based on Particle Swarm Optimization Algorithm with Improved Inertia Weights

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Wei Xie ◽  
Jie-Sheng Wang ◽  
Hai-Bo Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Dc Motor ◽  
Pi Controller ◽  
Brushless Dc Motor ◽  
Swarm Optimization ◽  
Brushless Dc ◽  
Inertia Weight ◽  
Speed Regulation

The brushless director current (DC) motor is a new type of mechatronic motor that has been developed rapidly with the development of power electronics technology and the emergence of new permanent magnet materials. Based on the speed regulation characteristics, speed regulation strategy, and mathematical model of brushless DC motor, a parameter optimization method of proportional-integral (PI) controller on speed regulation for the brushless DC motor based on particle swarm optimization (PSO) algorithm with variable inertia weights is proposed. The parameters of PI controller are optimized by PSO algorithm with five inertia weight adjustment strategies (linear descending inertia weight, linear differential descending inertia weight, incremental-decremented inertia weight, nonlinear descending inertia weight with threshold, and nonlinear descending inertia weight with control factor). The effectiveness of the proposed method is verified by the simulation experiments and the related simulation results.

scholarly journals Efficiency of particle swarm optimization applied on fuzzy logic DC motor speed control

2008 ◽  
Vol 5 (2) ◽  
pp. 247-262 ◽  
Author(s):  
Boumediene Allaoua ◽  
Abderrahmani Abdessalam ◽  
Gasbaoui Brahim ◽  
Nasri Abdelfatah
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Speed Control ◽  
Dc Motor ◽  
Motor Speed ◽  
Swarm Optimization

Multi-objective collaborative multidisciplinary design optimization using particle swarm techniques and fuzzy decision making

2012 ◽  
Vol 226 (9) ◽  
pp. 2281-2295 ◽  
Author(s):  
Mohammad Reza Farmani ◽  
Jafar Roshanian ◽  
Meisam Babaie ◽  
Parviz M Zadeh
Keyword(s):  
Particle Swarm Optimization ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Fuzzy Decision ◽  
Swarm Optimization ◽  
Multi Objective

This article focuses on the efficient multi-objective particle swarm optimization algorithm to solve multidisciplinary design optimization problems. The objective is to extend the formulation of collaborative optimization which has been widely used to solve single-objective optimization problems. To examine the proposed structure, racecar design problem is taken as an example of application for three objective functions. In addition, a fuzzy decision maker is applied to select the best solution along the pareto front based on the defined criteria. The results are compared to the traditional optimization, and collaborative optimization formulations that do not use multi-objective particle swarm optimization. It is shown that the integration of multi-objective particle swarm optimization into collaborative optimization provides an efficient framework for design and analysis of hierarchical multidisciplinary design optimization problems.

Sign in / Sign up

Export Citation Format

Share Document