A robust real time position and force (hybrid) control of a robot manipulator in presence of uncertainties

Abstract

We examine the living intelligent biological systems and model the computational system components. We consider the situation of a kind of "blind-tracking" with constant force/torque by a human hand. The problem involves hand kinematics, hand motor control, and an adaptive judgment method from the position and force/torque reflection of the uncertain hyper plane. In this study, these control levels were designed using neural networks and fuzzy logic technologies. The control levels are coordinated amongst themselves forming the distributed artificial intelligent (DAI) system. The conclusive characteristic of the proposed controller was a one-step-ahead feedback control. This DAI-based control systems was implemented in the RX-90 industrial robot. Certainly these types of control system will help an industry to be autonomous and increase the productivity as well.