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- W2070292646 abstract "We present a state-feedback control of a two-link flexible-joint robot. The control algorithm does not require the mathematical model representing the robot. Three-layer neural networks approximate the unknown plant functions. The neural network weights are adapted on-line. We use backstepping control structure. We use variable structure control to provide robustness to all uncertainties. For simulation, we obtain parameter values of the Euler-Lagrange model from real experiment. We, then, add backlash, deadzone, and additive disturbances to the Euler-Lagrange model to closely replicate the actual robot. We show through simulation that our controller can handle these actuator nonlinearities effectively." @default.
- W2070292646 created "2016-06-24" @default.
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- W2070292646 date "2005-01-01" @default.
- W2070292646 modified "2023-09-24" @default.
- W2070292646 title "Motion control of two-link flexible-joint robot with actuator nonlinearities, using backstepping and neural networks" @default.
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- W2070292646 doi "https://doi.org/10.1109/iros.2005.1545310" @default.
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