The availability of renewable energy does not meet the demands of consumption. Hence, fossil fuels will continue to be an important energy source, and coal promises to cover the requirements for the coming decades. Because of its high energy content, deep lying bituminous coal and anthracite are important for energy generation. One trend in the future of coal mining is thin seam mining, because thick seams more and more have been exploited. A well-known and approved longwall mining method for thin seams is plowing which has big advantages compared to a shearer because of its compact design. The extraction of those thinner coal seams will become more and more important in coal industry and therefore the plow will receive more attention in future. Most approaches in longwall automation are focused on the shearer and need a more or less intelligent exploitation machine. Therefore those approaches cannot be used for the plow technology. The authors introduce a shield-data-based horizon control (SDHC). The developed approach integrates the shield data provided by the roof support and process monitoring into the horizon control process to keep the plow in seam even if the seam trend changes. This control concept can be used for the shearer as well as for the plow. The basic idea of SDHC for plow application will be introduced in this paper and first simulation results will be shown.
This paper presents a method for actively controlling torsional vibrations in rotating machines caused by angledependent parameters. The work is motivated by rotating machines with crank or cam gear mechanisms that cause fluctuations in the angular speed when the machine is driven by a constant load torque or when the speed is controlled with conventional controllers. A very general model for such a system is introduced and used to derive a control law by feedback linearization. With this control law, the speed fluctuations are completely eliminated and desired linear dynamics can be prescribed for the system. The method is tested in a simulation study with a model of a real industrial machine. Although the proposed method works well, the study is preliminary in the sense that the method has not been applied experimentally and its robustness has not been assessed.
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