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

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.