Journal of Astronautics ›› 2015, Vol. 36 ›› Issue (12): 1391-1397.doi: 10.3873/j.issn.1000-1328.2015.12.007

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Adaptive Network Control of Flexible Joint Space Manipulator in Task Space under Gravity Effect

LIU Fu cai, GAO Jing fang, JIA Xiao jing   

  1. Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China
  • Received:2014-12-22 Revised:2015-03-17 Online:2015-12-15 Published:2015-12-25

Abstract:

Aiming at trajectory tracking of flexible-joint space robot affected by gravity uncertainties, a neural network adaptive control algorithm in task space is proposed for flexible-joint space robot based on singular perturbation theory in this paper. Fristly the model of flexible-joint robot is established, then the system order is reduced by using the singular perturbation method and the dynamics is transformed from joint space to task space, and an adaptive neural control algorithm is designed to approximate the system uncertainty, last the control quantities as the motor control torques is transformed from task space to joint space. The stability analysis is presented, and the effectiveness of the scheme is verified by the corresponding simulation results. The controller can solve both high frequency resonance and instability problems caused by flexible-joint, and also it can resist the disturbance such as gravity effectively and has good tracking performance .

Key words: Flexible-joint, Gravity effect, RBF neural network, Singular perturbation, Task space

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