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Adaptive Finite-time Tracking Control for a Robotic Manipulator with Unknown Deadzone
文件大小：
486k
资源说明：This paper is concerned with the adaptive finitetime
control for a robotic manipulator preceded by unknown
non-symmetric deadzone. Radial basis function neural networks
(RBFNNs) are employed to approximate the unknown dynamics
and the deadzone effect of actuators. Adaptive finite-time
tracking controller is then proposed based on the finite-time
stability theorem in combination with backstepping technique.
Consequently, tracking control of a robotic manipulator
control for a robotic manipulator preceded by unknown
non-symmetric deadzone. Radial basis function neural networks
(RBFNNs) are employed to approximate the unknown dynamics
and the deadzone effect of actuators. Adaptive finite-time
tracking controller is then proposed based on the finite-time
stability theorem in combination with backstepping technique.
Consequently, tracking control of a robotic manipulator
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