Stiffness control of robot manipulators in the operational space using fuzzy mapping of dynamic functions

In this paper a stiffness control strategy based on the fuzzy mapped nonlinear terms of the robot manipulator dynamic model is proposed. The proposed stiffness controller is evaluated on a research robot manipulator performing a task in the operational space. Tests attempted to achieve fast motion with reasonable accuracy associated with lower computational load compared to the non-fuzzy approach. The stability analysis is presented to conclude about the mapping error influence and to obtain precondition criteria for the gains adjustment to face the trajectory tracking problem. Simulation results that supported the implementation are presented, followed by experiments and results obtained. These tests are conducted on a robot manipulator with SCARA configuration to illustrate the feasibility of this strategy.