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Open AccessArticle

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
Micromachines 2016, 7(9), 168; https://doi.org/10.3390/mi7090168
Received: 1 July 2016 / Revised: 30 August 2016 / Accepted: 1 September 2016 / Published: 15 September 2016
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)
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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.

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