Due to their compliant structure, industrial robots without precision-enhancing measures are only to a limited extent suitable for machining applications. Apart from structural, thermal and bearing deformations, the main cause for compliant structure is backlash of transmission drives. This paper proposes a method to improve trajectory tracking accuracy by using secondary encoders and applying a feedback and a flatness based feed forward control strategy. For this purpose, a novel nonlinear, continuously differentiable dynamical model of a flexible robot joint is presented. The robot joint is modeled as a two-mass oscillator with pose-dependent inertia, nonlinear friction and nonlinear stiffness, including backlash. A flatness based feed forward control is designed to improve the guiding behaviour and a feedback controller, based on secondary encoders, is implemented for disturbance compensation. Using Automatic Differentiation, the nonlinear feed forward controller can be computed in a few microseconds online. Finally, the proposed algorithms are evaluated in simulations and experimentally on a real KUKA Quantec KR300 Ultra SE.

由于其柔顺的结构，没有精确增强措施的工业机器人仅在有限的程度上适用于机械加工应用。除了结构，热和轴承变形外，柔顺结构的主要原因还在于传动装置的间隙。本文提出了一种通过使用次级编码器并应用基于反馈和平坦度的前馈控制策略来提高轨迹跟踪精度的方法。为此，提出了一种新颖的非线性，柔性机器人关节的连续可微动力学模型。机器人关节被建模为具有姿态依赖的惯性，非线性摩擦和非线性刚度（包括反冲）的两质量振荡器。基于平面度的前馈控制旨在改善导向性能和反馈控制器，基于辅助编码器的系统，用于干扰补偿。使用自动微分，可以在几微秒内在线计算非线性前馈控制器。最后，在真实的KUKA Quantec KR300 Ultra SE上通过仿真和实验对提出的算法进行了评估。