Comparison of Singular Perturbations Approximation Method and Meta-Heuristic-Based Techniques for Order Reduction of Linear Discrete Systems
Applied and Computational Mathematics
Volume 6, Issue 4-1, July 2017, Pages: 48-54
Received: Aug. 16, 2016; Accepted: Sep. 12, 2016; Published: Dec. 8, 2016
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Anouar Bouazza, Department of Electrical Engineering, National Engineering School of Monastir, Sousse, Tunisia
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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.
Order Reduction Techniques, Singular Perturbations Approximations Method, Meta-Heuristics Methods, Particle Swarm Optimization, Shuffled Frog Leaping Algorithm
To cite this article
Anouar Bouazza, Comparison of Singular Perturbations Approximation Method and Meta-Heuristic-Based Techniques for Order Reduction of Linear Discrete Systems, Applied and Computational Mathematics. Special Issue:Some Novel Algorithms for Global Optimization and Relevant Subjects. Vol. 6, No. 4-1, 2017, pp. 48-54. doi: 10.11648/j.acm.s.2017060401.14
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