Uncertainties play a fundamental role in systems design, since the device behavior may be undesirable in the presence of unknown parameters. For devices interacting with humans, the force exerted by different operators represents a source of uncertainty, which under specific circumstances, could lead to undesired performance. This article proposes a robust concurrent design of a planar 2-DOF cobot modeled as a differential algebraic system and considers the force exerted by the human operator as the output of a PD controller. The robust concurrent design keeps the system performance as less sensitive as possible despite the different operators that interact with the device. Therefore, we establish the robust concurrent design as a multiobjective dynamic optimization problem, intended to minimize both the trajectory tracking error and its sensitivity with respect to uncertain parameters. The source of uncertainty comes from the force applied by the human operator while the independent variables are the inertial and kinematic parameters of the links in the kinematic chain, as well as the cobot controller gains. Experimental results show the effectiveness of the proposed design methodology.

中文翻译：

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两自由度协作机器人（Cobot）的鲁棒并行设计

不确定性在系统设计中起着根本性的作用，因为在存在未知参数的情况下设备的行为可能是不希望的。对于与人互动的设备，不同操作员施加的力量是不确定性的根源，在特定情况下，这可能会导致不良性能。本文提出了一种建模为差分代数系统的平面2-DOF协作机器人的鲁棒并行设计，并将人工操作人员施加的力视为PD控制器的输出。健壮的并发设计使系统性能尽可能不敏感，尽管与设备交互的操作员有所不同。因此，我们将健壮的并行设计建立为多目标动态优化问题，旨在最小化轨迹跟踪误差及其对不确定参数的敏感性。不确定性源于操作员施加的力，而自变量是运动链中链节的惯性和运动学参数，以及cobot控制器的增益。实验结果表明了所提出的设计方法的有效性。