Identification and modeling of 3-DoF mechanism with nonlinear friction effects by combination of LuGre and neural network modeling

Abstract

Many mechanical systems suffer from strong passive effects due to presence of various imperfect kinematic joints and bearings. Such effects are more crucial for free oscillation systems or vibration absorbers since their ideal design should be as friction free as possible to work properly. To be able to deal with such inconveniences, it is first necessary to describe passive effects acting to moving bodies of the mechanism. However, such forces are usually far from linear function of velocity and incorporates hysteresis, backlash, stick–slip or nonlinear functions of velocity as well as of position. Therefore, state-full friction model is needed. This paper deals with passive effects identification present in multi degrees of freedom absorber demonstrator’s kinematic joints. Such absorbers are suitable for absorbing spatially complex unwanted vibrations of robots and other complex mechanisms. For such identification purpose, the well known LuGre dynamical model of dissipative forces is firstly tested. Finally the absorber mechanism model with optimized LuGre models is extended by trained neural network improving the whole mechanism modeling in order to reach sufficient simulation corresponding to measured behavior of absorber. • Passive effects in three degrees of freedom vibration absorber identified. • The high nonlinearities in friction forces including stick–slip effects presented. • The novel friction forces model combining LuGre and neural network proposed. • The functionality successfully experimentally tested on demonstrator of absorber.