Model Reduction via Particle Swarm Optimization (PSO)

M. Abdalla (Jordan)

Keywords

Model Reduction, Reducibility Matrix, LMI, SingularPerturbation, Particle Swarm Optimization.

Abstract

A novel technique in system model reduction is expanded by the use of Particle Swarm Optimization (PSO) to tune some of the coupling terms parameters. The proposed method is derived using the matrix reducibility technique concept. The main advantage of this reduction scheme is the ability to preserve selected eigenvalues of the full model and to introduce them onto the reduced model. This preservation of the eigenvalues is the key to making the mathematical model look more realistic and closer to the physical model. Finally, the outcomes of this method are fully illustrated using simulations and are compared with other model reduction methods.

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