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