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Piecewise Modeling Based on Particle Swarm Optimization Algorithm Using Numerical Data (644.7Kb)
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Title
Piecewise Modeling Based on Particle Swarm Optimization Algorithm Using Numerical Data
Author
Taniguchi, Tadanari
Eciolaza, LukaORCID
Research Group
Robótica y Automatización
Other institutions
https://ror.org/01p7qe739
Version
Published version
Document type
Conference Object
Embargo end date
2144-01-01
Language
English
Rights
© 2024 IEEE
Access
Embargoed access
URI
https://hdl.handle.net/20.500.11984/14536
Publisher’s version
https://doi.org/10.1109/FUZZ-IEEE60900.2024.10612184
Published at
IEEE International Conference on Fuzzy Systems  2024 (FUZZ-IEEE). Yokohama, Japan
Publisher
IEEE
Keywords
nonlinear system
particle swarm optimization
piecewise modeling
Subject (UNESCO Thesaurus)
Automatic control
Robotics
Abstract
We propose a piecewise modeling method using numerical data. The shape of the piecewise model is a rectangular form into a state-space. The vertex values of the rectangular regions are determined usin ... [+]
We propose a piecewise modeling method using numerical data. The shape of the piecewise model is a rectangular form into a state-space. The vertex values of the rectangular regions are determined using particle swarm optimization because the optimal dividing solution is a nonlinear programming problem. Using the particle swarm optimization as a multi-point search algorithm, the proposed method can determine optimal vertex values of the piecewise regions with minimal modeling errors. This paper considers some examples to demonstrate the effectiveness of the proposed method using numerical simulations. [-]
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