Robust Control and Adaptive Robust Control for Robot Manipulators.

On the assumption that the exact model of manipulators is never known and only the estimated model is obtained with some errors, a new robust and a new adaptive robust control schemes are proposed to achieve the specified tracking precision. These schemes are derived based on Lyapunov stability theory. The robust control needs the upper bound of errors between the estimated model and the real one, and then it uses a relatively high gain feedback. The adaptive robust control does not need the error bound, but it makes an on-line estimation for the feedback gain. It is an improvement on traditional methods to relieve a problematical assumption. Comparing with adaptive control scheme, In which all the physical parameters are on-line estimated, the adaptive robust control is robust to unexpected disturbance. The effectiveness is verified by experiments.