Adaptive Force-Vision Control of Robot Manipulator Using Sliding Mode and Fuzzy Logic

Abstract

An adaptive sliding mode controller based on fuzzy logic is proposed to control a manipulator robot over unknown surface trajectory using force-vision tracking, considering uncertainties of the kinematic, dynamic, and camera models. In this work we show that the robot can track the desired trajectories overcoming the model’s uncertainties, the use of the sliding mode to reject the disturbances and converge much faster, a nonlinear sliding surface proposed to regulate the convergence speed in order to illuminate the overshoot of the system response, thanks to the online fuzzy logic adaption, used to generate the equivalent control. The system’s stability has been validated using Lyapunov criteria. So as to show the performance of the proposed control law, we performed simulations consisting of a series of tests in various conditions. The obtained results allowed us to validate the robustness of the controller towards the payload variations and the model’s uncertainties.