Adaptive Inverse Control for Gripper Rotating System in Heavy-Duty Manipulators With Unknown Dead Zones

The gripper rotation system of a heavy-duty manipulator is generally driven by hydraulic motors, and it is difficult to guarantee the accuracy of the rotation angle using conventional control methods due to the existence of dead zones with unknown characteristics. This paper proposes an adaptive inverse dead-zone control method, in which the gradient projection technique is applied to design an adaptive updating law for estimating the inverse dead-zone parameters online. First, a dynamic model of the gripper rotation system is presented with an analysis of its dead-zone characteristics. Then, the controller is designed based on a Takagi-Sugeno fuzzy model, and the estimated values of the inverse dead-zone parameters are shown to converge to their true values. Finally, the performance of the proposed adaptive control method is experimentally demonstrated on an actual forging manipulator. Comparisons with a fixed inverse dead-zone control method demonstrate the effectiveness and applicability of the proposed control method.