Robust Adaptive Control for Robotic System with External Disturbance and Guaranteed Parameter Estimation

Abstract

Robotic system is an essential part of industrial production, which can perform a variety of tasks and operations. However, due to the existence of various nonlinearities, uncertainties, and external disturbance in the robotic system, it is a challenge to achieve system stability and the accurate tracking performance. This paper proposes a novel robust adaptive control for the robotic system to handle the unknown system parameters and external disturbance. An auxiliary filter is developed to derive the linear parameterized representation of the system without using the measurement of the acceleration signal, which is also combined with an adaptive law to guarantee the exponential convergence of the estimation error. For the external disturbance, a robust term is incorporated into the controller to compensate for the influence of the external disturbance. Finally, comparative simulations are conducted to verify the effectiveness and advantages of the proposed control approach.