  This paper proposes a friction model parameter identification routine that
can work with highly nonlinear and chaotic systems. The chosen system for this
study is a passively-actuated tilted Furuta pendulum, which is known to have a
highly non linear and coupled model. The pendulum is tilted to ensure the
existence of a stable equilibrium configuration for all its degrees of freedom,
and the link weights are the only external forces applied to the system. A
nonlinear analytical model of the pendulum is derived, and a continuous
friction model considering static friction, dynamic friction, viscous friction,
and the stribeck effect is selected from the literature. A high-gain Universal
Adaptive Stabilizer (UAS) observer is designed to identify friction model
parameters using joint angle measurements. The methodology is tested in
simulation and validated on an experimental setup. Despite the high
nonlinearity of the system, the methodology is proven to converge to the exact
parameter values, in simulation, and to yield qualitative parameter magnitudes
in experiments where the goodness of fit was around 85\% on average. The
discrepancy between the simulation and the experimental results is attributed
to the limitations of the friction model. The main advantage of the proposed
method is the significant reduction in computational needs and the time
required relative to conventional optimization-based identification routines.
The proposed approach yielded more than 99\% reduction in the estimation time
while being considerably more accurate than the optimization approach in every
test performed. One more advantage is that the approach can be easily adapted
to fit other models to experimental data.
