Control of an Industrial PA10-7CE Robot Arm Based on Decentralized Neural Backstepping Approach

Authors:
R. Garcia -Hernandez;E. N. Sanchez;J. L. -Lara;J. A. -Hernandez
Affiliations:
Facultad de Ingenieria, Universidad Autonoma del Carmen, Campeche, Mexico C.P. 24180;Department of Electrical Engineering, CINVESTAV Unidad Guadalajara, Jalisco, Mexico C.P. 45019;Facultad de Ingenieria, Universidad Autonoma del Carmen, Campeche, Mexico C.P. 24180;Facultad de Ingenieria, Universidad Autonoma del Carmen, Campeche, Mexico C.P. 24180
Venue:
Neural Processing Letters
Year:
2013

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Abstract

This paper presents a discrete-time decentralized control strategy for trajectory tracking of a Mitsubishi PA10-7CE robot arm. A high order neural network is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form. The weights for each neural network are adapted online by extended Kalman filter training algorithm. The motion of each joint is controlled independently using only local angular position and velocity measurements. The stability analysis for closed-loop system via Lyapunov theory is included. Finally, the simulations results show the feasibility of the proposed scheme.