Developingan adaptive controller based on cerebellar model


Abstract in English

In this study we developed an adaptive model inspired by internal models in the cerebellum and this approach called Feedback Error Learning (FEL). FEL is the origin of Learning Feed-Forward Control (LFFC). It depends on Feedback Controller and Feed-Forward Controller which is a Neural Network, and this Neural Network uses feedback controller output as training signal. We developed this approach to control a robot arm, and to balance inverted pendulum and to control bus suspension system. We developed this approach by adding a second Neural Network, and this new Neural Network uses FEL controller output as training signal. We simulate these systems by using Matlab and Simulink, and we find that this development improves control performance.

References used

KAWATO, M.; FURUKAWA, K., and SUZUKI, R. A hierarchical neural-network model for control and learning of voluntary movements. Biol. Cybernet. 57,1987, 169–185
KAWATO, M., and GOMI, H. A computational model of four regions of the cerebellum based on feedback error learning. Biol. Cybern. 68, ,1992, 95–103
KAWATO, M. Internal models for motor control and trajectory planning. Curr. Opin. Neurobiol. 9 ,1999, 718–727
ALBUS, J.S. A new approach to manipulator control: the cerebellar model articulation controller (CMAC). J. Dyn. Sys. Meas. Contr. 97, 1975, 220–227

Download