Deterministic learning from robust adaptive NN control of robot manipulators

@article{Wang2010DeterministicLF,
  title={Deterministic learning from robust adaptive NN control of robot manipulators},
  author={Cong Wang and Wujun Gu and Zhengui Xue},
  journal={2010 8th World Congress on Intelligent Control and Automation},
  year={2010},
  pages={526-531}
}
We investigate the learning issue in the robust adaptive neural-network (NN) control process of manipulator with unknown system dynamics and disturbance. Based on recently developed deterministic theory, the regression vector of an appropriately designed robust adaptive NN controller satisfies the partial persistent exciting (PE) condition when tracking a periodic or periodic-like reference orbit, and partial convergence of NN weights can be achieved when the disturbance term is small in the… CONTINUE READING
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Nonlinear Systems

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