Title :
A Model of Feedback Error Learning Based on Kalman Estimator
Author :
Ruan, Xiaogang ; Liu, Liang ; Yu, Naigong ; Ding, Mingxiao
Author_Institution :
Dept. of Electron. Inf. & Control Eng., Beijing Univ. of Technol.
Abstract :
Based on the feedback error learning (FEL) method and Michael et al.´s research work on dynamical state estimation, a new model of motor control system is proposed to overcome the drawback deriving from time delay. In the new model, the supervised signal derives from both the output of the Kalman estimator and the feedback motor command, and this comprehensive signal provides the instructive information to train the forward neural network in the cerebellar cortex. The effectiveness of the proposed new model is demonstrated by simulation experiments on inverted pendulum
Keywords :
feedback; feedforward neural nets; nonlinear systems; state estimation; Kalman estimator; cerebellar cortex; dynamical state estimation; feedback error learning; feedback motor command; forward neural network; inverted pendulum; motor control system; time delay; Brain modeling; Delay effects; Error correction; Kalman filters; Motor drives; Neural networks; Neurofeedback; Output feedback; State estimation; State feedback; Kalman filter; cerebellum; feedback error learning; internal mode; state estimation;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713164
