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Adaptive Tracking Control of Hybrid Machines: A Closed-Chain Five-Bar Mechanism Case

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6 Author(s)
Long Cheng ; Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China ; Yingzi Lin ; Zeng-Guang Hou ; Min Tan
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This paper considers the trajectory tracking problem of hybrid machines. A hybrid machine here refers to a machine that is driven by the constant velocity (CV) motors and servomotors in a proper configuration. The hybrid machine is a meaningful tradeoff between task flexibility and power capacity. However, this system has brought a new challenge to control due to the velocity fluctuation in the CV motor. The velocity fluctuation problem is caused mainly by the uncontrollable input current and the time-varying workload. In addition, the dynamic parameters are uncertain, which further increases the control difficulty. In this paper, we propose an adaptive control law for the trajectory tracking and demonstrate the effectiveness of this control law on a 2-DOF closed-chain five-bar hybrid mechanism driven by one servomotor and one CV motor. The principle of the proposed controller is to properly design the servomotor control input that can compensate not only the uncertainty in the servomotor but also the uncertainty in the CV motor. By the proposed adaptive control law, it can be theoretically proved that the position/velocity tracking errors of the joint associated with the servomotor and the velocity tracking error of the joint associated with the CV motor are convergent to zero as time goes to infinity. Finally, the simulation examples are given to illustrate the effectiveness of the proposed method.

Published in:

IEEE/ASME Transactions on Mechatronics  (Volume:16 ,  Issue: 6 )