MoRC is a high-performance modular robot controller based on the Functional Mock-up Interface (FMI) standard. The goal is to control any (industrial) robot with electrical drives using a customizable vendor-agnostic control cabinet and an innovative, self-developed software architecture based on exchangeable multi-rate real-time control components with standardized interfaces. On the hardware side, the use of EtherCAT (Ethernet for Control Automation Technology) allows connecting a freely selectable number of COTS (commercial off-the-shelf) electrical drives and sensors. On the software side, this is matched with exchangeable control software modules based on the FMI standard. Those can be interconnected for forming user-defined multi-rate control structures which can be executed as synchronized real-time threads on a central Linux-based multi-core computing unit. That unlocks additional computational potential for advanced high-frequency control algorithms. Control structures can be switched at runtime to handle highly diverse control tasks. This paper presents the architectural concepts as well as first experiments on an industrial robot testbed.

Subject of this paper is an industrial gantry robot with elastic behavior. To suppress residual vibrations command shaping filters are widely used. These filters, however, change the shape and duration of the originally commanded trajectory. Therefore, a command shaping filter is proposed which is based on the inverse model of the flexible robot dynamics. To that end, a planar dynamics model of the robot is derived which is suitable for control design. It captures the relevant dynamics of vibrations including the non-minimum phase characteristics. Based on the inverse dynamics, a feedforward filter for vibration suppression is developed. The tracking error due to filter delay is reduced compared to other command shaping techniques. The non-minimum phase properties of the flexible dynamics are avoided by using a virtual reference point for plant inversion. Experimental results show the effectiveness of the proposed Inverse Model Command Shaper compared to other types of filters tuned for vibration suppression.