Abstract
An indirect adaptive control approach is developed in this paper for robots with unknown nonlinear dynamics using neural networks (NNs). A key property of the proposed approach is that the actual joint angle values in the control law are replaced by the desired joint angles, angle velocities and accelerators, and the bound on the NN reconstruction errors is assumed to be unknown. Main theoretical results for designing such a neuro-controller are given, and the control performance of the proposed controller is verified with simulation studies.
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Sun, F., Sun, Z., Zhu, Y. et al. Stable Neuro-Adaptive Control for Robots with the Upper Bound Estimation on the Neural Approximation Errors. Journal of Intelligent and Robotic Systems 26, 91–100 (1999). https://doi.org/10.1023/A:1008195720685
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DOI: https://doi.org/10.1023/A:1008195720685