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首页> 外文期刊>Mechatronics, IEEE/ASME Transactions on >Adaptive Tracking Control of Hybrid Machines: A Closed-Chain Five-Bar Mechanism Case
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Adaptive Tracking Control of Hybrid Machines: A Closed-Chain Five-Bar Mechanism Case

机译：混合动力机器的自适应跟踪控制：闭链五连杆机构案例

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摘要

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.
机译：本文考虑了混合动力机器的轨迹跟踪问题。混合动力机是指以适当的配置由恒速（CV）电动机和伺服电动机驱动的机械。混合动力机器是任务灵活性和功率容量之间有意义的折衷方案。但是，由于CV电动机的速度波动，该系统给控制带来了新的挑战。速度波动问题主要是由无法控制的输入电流和时变工作量引起的。另外，动态参数是不确定的，这进一步增加了控制难度。在本文中，我们提出了一种用于轨迹跟踪的自适应控制律，并证明了该控制律在由一台伺服电动机和一台CV电动机驱动的2-DOF闭链五杆混合机构上的有效性。提出的控制器的原理是正确设计伺服电机控制输入，该输入不仅可以补偿伺服电机中的不确定性，而且可以补偿CV电机中的不确定性。通过提出的自适应控制定律，从理论上可以证明，随着时间的推移，与伺服电机相关联的关节的位置/速度跟踪误差和与CV电机相关联的关节的速度跟踪误差都收敛为零。最后，通过仿真实例说明了该方法的有效性。

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