Advanced Neuro-Fuzzy System in the Task of Position-Force Control of a Manipulator

Abstract

The article presents an application of the hybrid neuro-fuzzy system in the task of position-force control of a robotic manipulator. The position-force control is especially important when the interaction force between the manipulator and its environment are large. This control problem relies on simultaneous execution of interacting forces between the manipulator’s tip, environment and the realisation path along the contact surface. Realisation of many robotised processes requires an application of the hybrid position-force control to perform the desired trajectory of the manipulator’s tip. This trajectory is associated with the contact surface geometry, and the desired down-force of the tip. In the article, the advanced neuro-fuzzy control system for the manipulator’s nonlinearities compensation is used.