Abstract
In this paper is proposed a control structure integrating fuzzy adaptive and fuzzy robust position and force control, in an explicit position based force control strategy, to compensate for modeling uncertainties of the manipulator and environment. The fuzzy robust controller is a position controller in the inner control loop, to compensate for uncertainties in the robot manipulator model. The control surfaces in the boundary layers are designed, so that the region near the origin of the state space can be reached faster. The fuzzy adaptive controller in the outer loop adjusts the manipulator tip position to compensate for uncertainties in the environment (stiffness and geometric location) with the purpose of reducing the error force. It uses a fuzzy inverse model and a learning mechanism to adapt the membership functions of the fuzzy logic controller. To show the performance on tracking force/position trajectories and to validate the proposed control structure scheme, simulations results are presented with a three degree of freedom manipulator.
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