Along with the traditional motion control demands, human–machine collaboration properties are becoming increasingly important in modern robotic control system. The collaboration requires both robot's dynamics and payload dynamics, in which the former can be identified offline, whereas the latter has to be estimated online. However, the accurate payload estimation cannot be guaranteed by the traditional adaptive control where the adaptation law and the control law are synthesized together to achieve the same goal of reducing tracking errors. To achieve precision motion control and accurate payload estimation simultaneously, this article first developed an identification method for a 6-DoFs industrial robot, which simplifies the excitation trajectory optimization and captures the main dynamics using fewer parameters; and then proposed an integrated direct/indirect adaptive robust control (DIARC) algorithm. Specifically, the proposed DIARC consists of a generalized momentum-based indirect adaptation law to estimate the payload online, a fast direct term to compensate for the adaptation transients, and a robust feedback to attenuate the uncertain nonlinearities. Finally, comparative experiments show that the payload is estimated to the true value and better tracking performances can be achieved by the proposed controller.

中文翻译：

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精确载荷估算的六自由度工业机器人的精确运动控制

随着传统运动控制需求的发展，人机协作特性在现代机器人控制系统中变得越来越重要。协作需要机器人动力学和有效载荷动力学，其中前者可以离线识别，而后者必须在线估计。然而，传统的自适应控制不能保证精确的有效载荷估计，在传统的自适应控制中，将自适应律和控制律综合在一起以实现减少跟踪误差的相同目标。为了同时实现精确的运动控制和精确的有效载荷估算，本文首先开发了一种六自由度工业机器人的识别方法，该方法简化了激励轨迹的优化过程，并使用较少的参数来捕获主要动态。然后提出了一种集成的直接/间接自适应鲁棒控制算法。具体而言，拟议的DIARC包括一个基于广义动量的间接自适应定律，用于在线估计有效载荷；一个快速直接项，用于补偿自适应瞬变；以及一个鲁棒的反馈，用于衰减不确定的非线性。最后，对比实验表明，该控制器可将有效载荷估算为真实值，并且可以实现更好的跟踪性能。