Z. Kovacic et al., A model reference & sensitivity model-based self-learning fuzzy logic controller as a solution for control of nonlinear servo systems, IEEE EN CON, 14(4), 1999, pp. 1479-1484
In this paper, design, simulation and experimental verification of a self-l
earning fuzzy logic controller (SLFLC) suitable for control of nonlinear se
rvo systems are described. The SLFLC contains a learning algorithm that uti
lizes a second-order reference model and a sensitivity model related to the
fuzzy controller parameters. The effectiveness of the proposed controller
has been tested in the position control loops of two chopper-fed de servo s
ystems, first by simulation in the presence of a backlash nonlinearity, the
n by experiment in the presence of a gravity-dependent shaft load and fairl
y high static friction. The simulation and experimental results have proved
that the SLFLC provides desired closed-loop behavior and eliminates a stea
dy-state position error.