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    Comparison of high performance hybrid variable reluctance fast steering mirrors

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    Actuated mirrors are a key element in free-space optical communications. This paper compares the two high performance, commercially available actuators with a hybrid variable reluctance drive principle. They feature a mechanical range of up to 3degrees and achieve closed-loop bandwidths of more than 1kHz in combination with eddy-current sensors. It is shown, that the choice of driver is closely linked to their achievable dynamics. In particular, the performance in the application area of optical communication on satellites is analyzed. Therefore, in addition to the dynamic properties, the integration, their power consumption and suppression of vibrations is also being considered. To ensure comparability, a parameter tuning algorithm is used. The breadboard utilizes the same control software and hardware for both devices. The FSM20B shows better passive rejection against external vibrations, a lower average power consumption, and allows the exchange of its angular sensors. The FSM3000 achieves a better steady-state jitter, features a larger operating range and is more compact in size with precalibrated, internal sensors

    Elastic Structure Preserving Control for Flexible Joint Robots With Position-Controlled Actuators

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    This article presents a novel control approach for flexible joint robots that use servo systems to control their motion. Under this configuration, the servo system is understood to have an inner feedback loop that accepts motor positions as inputs and uses torques as outputs. Hence, the soft robot uses motor positions as control inputs instead of torques. To address this system configuration with a reliable control system of high performance, we aim to generalize the elastic structure preserving (ESP) control approach, which previously has been proposed for backdrivable torque-controlled elastic robots, to robots with position-controlled elastic actuators. This scheme results in a dynamic feedback controller that recovers the elastic structure of the uncontrolled robot in the closed loop. At the same time, damping is injected, thus achieving a control system with high compliance and desired energy dissipation. Our results are supported by a rigorous analysis, where local input-to-state stability and output strict passivity can be concluded if the inner feedback loop from the servo system satisfies some assumptions. Experiments on two platforms validate the proposed control scheme and show the overall control system’s performance

    Demonstration of decentralized high-purity hydrogen production from wood chips for PEM-FC application

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    A 100 kWH2 demonstration plant for the production of high-purity hydrogen from wood chips, the BioH2Modul, and a proton exchange membrane fuel cell tractor, the FCTRAC, were developed and built to demonstrate a whole value chain for decentralized hydrogen production and on-site utilization. The circular economy approach proposes a holistic solution to the issue of defossilization in the agricultural and forestry sector. This work focuses on the hydrogen production process chain in which wood chips are converted by downdraft fixed-bed gasification into a product gas to be conditioned, cleaned, and upgraded to purified hydrogen. Commissioning of the fixed-bed gasifier, the water-gas shift unit, the water quench, the rapeseed methyl ester scrubber, the adsorber unit, and the compression unit was successfully completed, proving reliable operation. The two-staged water-gas shift unit converted about 93% of carbon monoxide, increasing the hydrogen content to 32.6 vol.-%db. In the downstream coarse gas cleaning units, 98% of ammonia and 90% of the tar compounds were separated. The separation efficiency for benzene amounted to 17%. The pressure swing adsorption unit was successfully coupled, but commissioning was not completed. However, previous pilot-scale test runs with a similar process chain proved the technical feasibility of high-purity hydrogen (= 99.97 vol.-% purity) production via downdraft fixed-bed gasification of wood chips

    Towards Autonomous Wood-Log Grasping with a Forestry Crane: Simulator and Benchmarking

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    Forestry machines operated in forest production environments face challenges when performing manipulation tasks, especially regarding the complicated dynamics of underactuated crane systems and the heavy weight of logs to be grasped. This study investigates the feasibility of using reinforcement learning for forestry crane manipulators in grasping and lifting heavy wood logs autonomously. We first build a simulator using Mujoco physics engine to create realistic scenarios, including modeling a forestry crane with 8 degrees of freedom from CAD data and wood logs of different sizes. We further implement a velocity controller for autonomous log grasping with deep reinforcement learning using a curriculum strategy. Utilizing our new simulator, the proposed control strategy exhibits a success rate of 96% when grasping logs of different diameters and under random initial configurations of the forestry crane. In addition, reward functions and reinforcement learning baselines are implemented to provide an open-source benchmark for the community in large-scale manipulation tasks. A video with several demonstrations can be seen at https://www.acin.tuwien.ac.at/en/d18a/

    Towards Implicit Coordination Planning with Knowledge and Belief

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    Numerical Solution of Singular ODEs

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