A new fuzzy method for the motion control of underactuated robots based on genetic algorithm

A new fuzzy method for the motion control of underactuated robots is proposed in this paper. The control objective is to move the end-effector from a given position to a target point. A new fuzzy controller for the motion control of underactuated robots is present. The best fuzzy control rules and optimal membership functions are automatically generated off-line by the global optimization of genetic algorithm. Because the proposed method does not make any hypothesis about the degree of freedom and unconsidering the rigorous linearizations to the original nonlinear system, it can be used without modification for arms with a large number of degree of freedom. At last, numerical simulations which are carried on the planar 2R underactuated robots show the effectiveness of the proposed method.