R. García-Hernández, E. Sánchez, V. Santibáñez, M. Llama, E. Bayro-Corrochano
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引用次数: 3
Abstract
This paper deals with adaptive trajectory tracking for discrete-time MIMO nonlinear systems. 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 proposed scheme is implemented in real-time to control a two DOF robot manipulator.
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