Lyapunov-based adaptive super-twisting control of a sandblasting and derusting parallel robot

Abstract

Aiming at the uncertainty problem existing in the sandblasting and derusting parallel robot (SDPR), including the jet reaction force (JRF) at the end of the spray gun, modeling errors and external disturbance, a robust trajectory tracking control is investigated. A calculation method for the JRF is proposed and the dynamic model of the SDPR considering the JRF is established to reduce the burden of controller design. Based on JRF compensation, an adaptive super-twisting control with no need for upper bound information of the system uncertainties is proposed. By adaptive adjustment of the control gain, the over-estimation of the gain is avoided, so the chattering of designed controller is suppressed while ensuring the system robustness. Lyapunov theory is applied to prove that the second order sliding mode can be established in finite time. Simulation results validate the effectiveness and superiority of the proposed control method.