A model-reference impedance control of robot manipulators using an adaptive fuzzy uncertainty estimator

This paper aims at developing a voltage -based impedance model-reference controller using fuzzy uncertainty estimator for the robust control of electrically driven robot manipulators. The proposed control scheme not only utilizes a desired impedance as a reference model, but also provides the integrated control of position and force in the closed loop system. The robotic system receives the output of model-reference as a desired trajectory and thus the aim of the controller is to reduce the difference between the task-space desired trajectory and the desired impedance model. Furthermore, two control terms namely a robustifying term and a fuzzy uncertainty estimator are added in the structure of control design in order to improve the performance of the control system as well as to tackle uncertainty including un-modelled dynamics and external disturbances. Using stability analysis, we derive the adaptive mechanisms and also prove the boundedness of all system states. Finally, simulation results are included to verify the proposed control method.