Robust Hybrid Position/Force Control with Adaptive Scheme

Abstract

When real robot manipulators are mathematically modeled, uncertainties are not avoidable. The uncertainties are often nonlinear and time varying. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance and etc. We proposed a class of robust hybrid position/force control of manipulators and provided the stability analysis in the previous work. In the work, we propose a class of adaptive robust hybrid position/force control of manipulators with bound estimation and the stability based on Lyapunov function is presented. Especially, this controller does not need the information of uncertainty bound. The simulation results are provided to show the effectiveness of the algorithm.

ANFIS PD+I Based Hybrid Force/ Position Control of an Industrial Robot Manipulator

“…An adaptive robust hybrid position/force control technique based on Lyapunov stability and bound estimation for a robot manipulator was proposed in [7]. The controller does not need the information of uncertainty bound.…”