Stable neuro-adaptive control for robot with unknown dynamics

An indirect adaptive control approach is developed in this paper for unknown robots using neural networks (NN). A key property of the proposed approach is that the actual joint angle values in the control law is replaced by the desired joint angle, angular speed and acceleration, and the bound on the NN reconstruction error is assumed to be unknown. Main theoretical results for designing such a neuro-adaptive controller are given, and the control performance of the proposed controller is verified with simulation studies.