R. García-Hernández, E. Sánchez, M. Saad, E. Bayro-Corrochano
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Discrete-time decentralized neural backstepping controller for a five DOF robot manipulator
This paper deals with adaptive trajectory tracking for a five DOF robot manipulator, A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The applicability of the proposed scheme is illustrated via simulations.
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