This paper presents a survey of Singular Perturbations Approximation (SPA) method and meta-heuristic techniques for order reduction of linear systems in discrete case. A comparison of intelligent techniques to determine the reduced order model of higher order linear systems is presented. Two approaches are considered: Particle Swarm Optimization (PSO) and Shuffled Frog Leaping Algorithm (SFLA). These methods are employed to reduce the higher order model and based on the minimization of the Mean Square Error (MSE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Each method is illustrated through numerical examples.
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Applied and Computational Mathematics (Volume 6, Issue 4-1)
This article belongs to the Special Issue Some Novel Algorithms for Global Optimization and Relevant Subjects |
| DOI | 10.11648/j.acm.s.2017060401.14 |
| Page(s) | 48-54 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2016. Published by Science Publishing Group |
Order Reduction Techniques, Singular Perturbations Approximations Method, Meta-Heuristics Methods, Particle Swarm Optimization, Shuffled Frog Leaping Algorithm
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APA Style
Anouar Bouazza. (2016). Comparison of Singular Perturbations Approximation Method and Meta-Heuristic-Based Techniques for Order Reduction of Linear Discrete Systems. Applied and Computational Mathematics, 6(4-1), 48-54. https://doi.org/10.11648/j.acm.s.2017060401.14
ACS Style
Anouar Bouazza. Comparison of Singular Perturbations Approximation Method and Meta-Heuristic-Based Techniques for Order Reduction of Linear Discrete Systems. Appl. Comput. Math. 2016, 6(4-1), 48-54. doi: 10.11648/j.acm.s.2017060401.14
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Download@article{10.11648/j.acm.s.2017060401.14,
author = {Anouar Bouazza},
title = {Comparison of Singular Perturbations Approximation Method and Meta-Heuristic-Based Techniques for Order Reduction of Linear Discrete Systems},
journal = {Applied and Computational Mathematics},
volume = {6},
number = {4-1},
pages = {48-54},
doi = {10.11648/j.acm.s.2017060401.14},
url = {https://doi.org/10.11648/j.acm.s.2017060401.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.s.2017060401.14},
abstract = {This paper presents a survey of Singular Perturbations Approximation (SPA) method and meta-heuristic techniques for order reduction of linear systems in discrete case. A comparison of intelligent techniques to determine the reduced order model of higher order linear systems is presented. Two approaches are considered: Particle Swarm Optimization (PSO) and Shuffled Frog Leaping Algorithm (SFLA). These methods are employed to reduce the higher order model and based on the minimization of the Mean Square Error (MSE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Each method is illustrated through numerical examples.},
year = {2016}
}
TY - JOUR T1 - Comparison of Singular Perturbations Approximation Method and Meta-Heuristic-Based Techniques for Order Reduction of Linear Discrete Systems AU - Anouar Bouazza Y1 - 2016/12/08 PY - 2016 N1 - https://doi.org/10.11648/j.acm.s.2017060401.14 DO - 10.11648/j.acm.s.2017060401.14 T2 - Applied and Computational Mathematics JF - Applied and Computational Mathematics JO - Applied and Computational Mathematics SP - 48 EP - 54 PB - Science Publishing Group SN - 2328-5613 UR - https://doi.org/10.11648/j.acm.s.2017060401.14 AB - This paper presents a survey of Singular Perturbations Approximation (SPA) method and meta-heuristic techniques for order reduction of linear systems in discrete case. A comparison of intelligent techniques to determine the reduced order model of higher order linear systems is presented. Two approaches are considered: Particle Swarm Optimization (PSO) and Shuffled Frog Leaping Algorithm (SFLA). These methods are employed to reduce the higher order model and based on the minimization of the Mean Square Error (MSE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Each method is illustrated through numerical examples. VL - 6 IS - 4-1 ER -
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