PD Control of robot with velocity estimation and uncertainties compensation

Authors:
W. Yu;X. Li
Affiliations:
Departamento de Control Automatico, CINVESTAV-IPN, México D.F., México;Sección de Computación, Departamento de Ingeniería Eléctrica, CINVESTAV-IPN, México D.F., México
Venue:
International Journal of Robotics and Automation
Year:
2006

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Abstract

Normal industrial PD control of Robot has two drawbacks: it needs joint velocity sensors, and it cannot guarantee zero steady-state error. In this paper we make two modifications to overcome these problems. High-gain observer is applied to estimate the joint velocities, and an RBF neural network is used to compensate gravity and friction. We give a new proof for high-gain observer, which explains a direct relation between observer gain and observer error. Based on Lyapunov-like analysis, we also prove the stability of the closed-loop system if the weights of RBF neural networks have certain learning rules and the observer is fast enough.