A setting method of initial conditions in particle swarm optimization for positioning of a linear stage

Marino Watanabe; Yukinori Nakamura; Shinji Wakui

doi:10.1109/ICIT.2015.7125077

A setting method of initial conditions in particle swarm optimization for positioning of a linear stage

Marino Watanabe, Yukinori Nakamura, Shinji Wakui

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

Abstract

This paper considers the auto-tuning of a feedforward controller in order to improve the performance of stage positioning. Particle swarm optimization (PSO) technique is employed for the auto-tuning of the controller. In the proposed method, firstly, the dimensionality of the particle in PSO is reduced. Then, the initial placement of each particle is determined by considering the nominal value of the stage. By using these two approaches, the tuning time can be shortened. After the auto-tuning, the settling time of the positioning is improved. Effectiveness of proposed methods is shown by simulation.

Original language	English
Pages	63-68
Number of pages	6
DOIs	https://doi.org/10.1109/ICIT.2015.7125077
Publication status	Published - Jun 16 2015
Externally published	Yes
Event	2015 IEEE International Conference on Industrial Technology, ICIT 2015 - Seville, Spain Duration: Mar 17 2015 → Mar 19 2015

Other

Other	2015 IEEE International Conference on Industrial Technology, ICIT 2015
Country/Territory	Spain
City	Seville
Period	3/17/15 → 3/19/15

ASJC Scopus subject areas

Computer Science Applications
Electrical and Electronic Engineering

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10.1109/ICIT.2015.7125077

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abstract = "This paper considers the auto-tuning of a feedforward controller in order to improve the performance of stage positioning. Particle swarm optimization (PSO) technique is employed for the auto-tuning of the controller. In the proposed method, firstly, the dimensionality of the particle in PSO is reduced. Then, the initial placement of each particle is determined by considering the nominal value of the stage. By using these two approaches, the tuning time can be shortened. After the auto-tuning, the settling time of the positioning is improved. Effectiveness of proposed methods is shown by simulation.",

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A setting method of initial conditions in particle swarm optimization for positioning of a linear stage

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