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Journal of Applied Mathematics
Volume 2012, Article ID 238563, 23 pages
Research Article

Bacterial Foraging-Tabu Search Metaheuristics for Identification of Nonlinear Friction Model

Power Electronics, Machines, and Control Research Group, Control and Automation Research Unit, School of Electrical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

Received 20 February 2012; Accepted 28 April 2012

Academic Editor: Hak-Keung Lam

Copyright © 2012 Nuapett Sarasiri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes new metaheuristic algorithms for an identification problem of nonlinear friction model. The proposed cooperative algorithms are formed from the bacterial foraging optimization (BFO) algorithm and the tabu search (TS). The paper reports the search comparison studies of the BFO, the TS, the genetic algorithm (GA), and the proposed metaheuristics. Search performances are assessed by using surface optimization problems. The proposed algorithms show superiority among them. A real-world identification problem of the Stribeck friction model parameters is presented. Experimental setup and results are elaborated.