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A neural network based adaptive robot controller
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DOI：10.1007/BF00435721.png)
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Neural network based adaptive controllers have been shown to achieve much improved accuracy compared with traditional adaptive controllers when applied to trajectory tracking in robot manipulators. This paper describes a new Recursive Prediction Error technique for estimating network parameters which is more computationally efficient. Results show that this neural controller suppresses disturbances accurately and achieves very small errors between commanded and actual trajectories.
Keyword:
neural networks
adaptive robot control
recursive prediction error
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