Discrete time sliding mode control of robotic manipulators: Development and experimental validation

This paper presents a discrete-time sliding mode control based on prediction compensation of uncertainties for planar robotic manipulators. Autoregressive models, identified on-line by Kalman Filters, are used to learn about uncertainties affecting the system. The analysis of the control stability is given and the controller is evaluated on the ERICC robot arm. Experiments show that the proposed controller produces good trajectory tracking performance and it is robust in the presence of model inaccuracies.