Abstract
In this paper, a position/force hybrid control of a robotic manipulator based on a neural network model is proposed with consideration of the dynamics of objects and the orientations of the robotic manipulator. This propsed system consists of standard PID controller, the gains of which are augmented and adjusted depending on objects and orientations of manipulators through a process of learning.
The authors proposed a simular method previously for the force control of one degree-of-freedom manipulator. The proposed method shows the better performance than the coventional PID controller, yielding the wider range of aplications. This paper shows the similar structure of the controller via the neural network model applicable to the cases of the position/force hybrid control of multi degreesof-freedum manipulators. Simulations as well as experiments are carried out for the case of the two dimentional robotic manipulators. The results show the applicability and adaptability of the proposed method to the position/force hybrid control of manipulators.
