Simple linear joint controllers are still used in typical industrial robotic systems. The use of these controllers leads to non-negligible dynamic path deviations for applications that require high path accuracy. These deviations result from the strong influence of nonlinearities, such as multi-body dynamics and gear friction. Sophisticated nonlinear control algorithms, known from the literature, are still not used because they usually require an expensive change of the control architecture. Therefore, different compensation methods are compared in this paper which reduce the path deviations by correction of the desired trajectory. This means that no torque interface is required, only an interface for path corrections is necessary. Such an interface normally exists so that the methods can simply be implemented within standard industrial controls. Using the industrial robot Siemens manutec-r15 the methods are experimentally compared with respect to their efficiency and practical applicability. Starting from this, one method is chosen for application to the stateof-the-art industrial robot KUKA KR15. The algorithm is based on a complete nonlinear dynamic model of the robot. It is integrated into the standard control KRC1. The experimental results prove the efficiency and the industrial applicability of the method.
The compensation for friction or joint losses in robotic manipulators contributes to an important improvement of the control quality. Besides appropriate friction modeling, experimental identification of the model parameters is fundamental toward better control performance. Conventionally steady-state friction characteristics are investigated for mechanical systems in the first step. However, and due to the high kinematic coupling, such procedure is already complicated for complex multiple closed-loop mechanisms, like parallel manipulators. Actuation friction of such mechanisms becomes configuration dependent. This paper presents a methodology that deals with such challenge. The kinematic coupling is regarded in the friction model and therefore in the design of the experimental identification. With the proposed strategy, it is possible to identify the steady-state friction parameters independently from any knowledge about inertial or rigid-body dynamics. Friction models for sensorless passive joints can also be provided. Besides, the method is kept very practical, since there is no need for any additional hardware devices or interfaces than a standard industrial control. The suitability for the industrial field is proven by experimental application to PaLiDA that is a six degrees of freedom parallel manipulator equipped with linear directly driven actuators.
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