The static and dynamic behaviour of the deburring process is analysed and with the help of fuzzy logic a linguistic description of the process is established. A fuzzy force control strategy for robotic deburring based on a corrective position/force con- trol structure is put forward. This deburring strategy solves the problems of compensating positional inac- curacies and adjusting the feedrate according to un- known burr sizes in a systematic way. Experimental results have verified the effectiveness of the proposed deburring strategy.

A unified dynamic force control structure is proposed, based on which three force controllers with different dynamics compensations are developed. To deal with the instability problem caused by high environmental stiffness and the robustness problem introduced by model uncertainty, two adaptive force controllers are proposed. Some typical simulation results on a manipulator with three degrees of freedom are presented to test the effectiveness of and to make a performance comparison among these force controllers.>

An efficient self-tuning control design method for redundant robotic manipulators is presented. With the nominal torques compensating the nonlinear interactions among the joints, the complex nonlinear dynamic equations are linearized and a linear input-output perturbation difference model is developed. Based on which two self-tuning control schemes are proposed in joint and Cartesian spaces. The controller parameters are estimated by the recursive least squares identification algorithm, and the modification torques are generated by minimizing a generalized cost function. Some typical simulation results are presented to demonstrate the effectiveness of these self-tuning control schemes.>