Self-tuning fuzzy compensation based adaptive impedance controller for robotic machining

The interaction force and the environmental uncertainties and changes are the most challenges for robotic material removal process. A self-tuning fuzzy strategy is adopted to implement the on-line compensation for the static error caused by the traditional impedance controller to improve the control performance. The fuzzy controller is adjusted by an updating factor to select the most appropriate fuzzy rule based on the measured performance results. When the deviation of the desired and actual position becomes greater, the adaptive algorithm is used to compensate the position. In this way, the bigger burrs can be removed completely and the workpiece can avoid to be damaged when a cavity is encountered. The simulation is carried out to verify the effectiveness of the proposed method in robotic machining process, and the control performance is better than that of a traditional impedance controller.