Application of modified Stribeck model and simulated annealing genetic algorithm in friction parameter identification

Friction is quite common and inevitable in physical environments. During the process of friction, vibration and collision will bring large deviations to identification results. In this paper, friction process with the influence of vibration and collision as well as data collection are implemented. In terms of friction model, according to the theory of Fourier series, we can introduce sine filter terms into friction model to eliminate influence of vibration and collision on parameter identifications. To get a much more accurate and efficient algorithm of identification, we embed simulated annealing operator into a genetic algorithm to take the advantages of both genetic algorithm and simulated annealing algorithm. With the hybrid algorithm, the identification results of friction process under the influence of the vibration and collision can be determined effectively.

I. Introduction

The existence of friction severely limits the performance of the mechanical system and will cause great harm to the system. It could not only reduce the accuracy of the electrical systems, speed stability and other important indicators, but also make the system into a paralysis state. Therefore, it is necessary to use appropriate methods to eliminate adverse influences of friction, namely, friction compensation. The appropriate mathematical model and valid identification algorithm of model parameters are the important prerequisites for the friction compensation.