Next Article in Journal
Deformability-Based Electrokinetic Particle Separation
Next Article in Special Issue
In-Plane MEMS Shallow Arch Beam for Mechanical Memory
Previous Article in Journal
Rapid Capture and Analysis of Airborne Staphylococcus aureus in the Hospital Using a Microfluidic Chip
Previous Article in Special Issue
Resonance Spectrum Characteristics of Effective Electromechanical Coupling Coefficient of High-Overtone Bulk Acoustic Resonator
Article Menu

Export Article

Open AccessArticle
Micromachines 2016, 7(9), 168; doi:10.3390/mi7090168

PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design

1
Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam
2
Faculty of Electrical & Electronic Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
3
Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan 71005, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editors: Teen-Hang Meen, Shoou-Jinn Chang, Stephen D. Prior and Artde Donald Kin­Tak Lam
Received: 1 July 2016 / Revised: 30 August 2016 / Accepted: 1 September 2016 / Published: 15 September 2016
View Full-Text   |   Download PDF [1479 KB, uploaded 15 September 2016]   |  

Abstract

Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO)-based algorithm and the evolutionary programming (EP) algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models. View Full-Text
Keywords: particle swarm optimization (PSO)-based; evolutionary programming (EP); integral of the squared error (ISE); micro air vehicle (MAV) particle swarm optimization (PSO)-based; evolutionary programming (EP); integral of the squared error (ISE); micro air vehicle (MAV)
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Tran, H.-K.; Chiou, J.-S. PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design. Micromachines 2016, 7, 168.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Micromachines EISSN 2072-666X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top