Unscented Kalman Filter Based State and Parameter Estimation for Overhead Hoist Transfer Using LuGre Friction Model

摘要

The purpose of this paper is to investigate a method of parameter estimation for overhead hoist transfer vehicles (OHTV) used for carrying products in a factory. The OHTVs are driven by a driving wheel controlled by a velocity servo motor. In this paper, we consider a mathematical model of the OHTVs with the LuGre friction model, which is considered as the nonlinear system. Our approach is that the parameter estimation is achieved by introducing an unscented Kalman filter (UKF). The performance of the proposed method is demonstrated by performing numerical simulations. The numerical result shows that the estimated value of the parameter has converged to the true value with the small bias.