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Robust Adaptive Tracking Control Based on State Feedback Controller With Integrator Terms for Elastic Joint Robots With Uncertain Parameters

机译:参数不确定的弹性关节机器人基于积分器状态反馈控制器的鲁棒自适应跟踪控制

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摘要

This brief addresses a robust adaptive control scheme based on a cascaded structure with a full state feedback controller with integrator terms as inner control loop and computed torque as outer control loop for flexible joint robots. Together with integrator effect, the adaptive control law can enhance position accuracy under uncertainties of the robot model, especially, the high friction caused by harmonic drive with high gear ratio. In this brief, the adaptive friction compensation is designed based on the LuGre friction model, which exhibits some advantages compared with the static friction model (e.g., no chattering effect at zero motor velocity). Furthermore, structural oscillations of the link side can be effectively damped by using joint torque feedback in the state feedback controller. Therefore, the proposed adaptive control approach can simultaneously provide high control performance both in terms of the dynamic behavior and the position accuracy. Global asymptotic tracking is achieved for the complete controlled system. The system stability is derived using Lyapunov approaches and Barbalat's lemma. Experimental results validate the practical efficiency of the approach.
机译:本文简要介绍了基于级联结构的鲁棒自适应控制方案,该方案具有全状态反馈控制器,其中积分器项作为内部控制环,而计算出的转矩作为柔性关节机器人的外部控制环。结合积分效应,自适应控制定律可以提高机器人模型不确定性下的位置精度,尤其是高传动比的谐波驱动引起的高摩擦。在此简要介绍中,基于LuGre摩擦模型设计了自适应摩擦补偿,与静态摩擦模型相比,它具有一些优势(例如,零电动机速度下没有颤动效应)。此外,通过在状态反馈控制器中使用关节扭矩反馈,可以有效地抑制连杆侧的结构振动。因此,提出的自适应控制方法可以在动态行为和位置精度方面同时提供高控制性能。完整控制系统实现了全局渐近跟踪。系统稳定性是使用Lyapunov方法和Barbalat引理得出的。实验结果验证了该方法的实际有效性。

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