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Muschalski, Lars
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Publications (4/4 displayed)
- 2024Influence of process parameters on quality of aluminum High Pressure Die Casting (HPDC) parts manufactured with a novel vertical chambered machine
- 2024Influence of toughness modification of high temperature thermosetting resins on fiber-reinforced composites strengths
- 2024Integration of a renewable energy source within a process network for hybrid metal-thermoplastic composite structures
- 2022Steuerung von Compliant-Mechanismen durch Reinforcement Learning
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Steuerung von Compliant-Mechanismen durch Reinforcement Learning
Abstract
Controlling of compliant-mechanisms with reinforcement learning Driving compliant-mechanisms to target positions is particularly challenging since it is not or hardly possible to set up the inverse kinematics with analytical models. On the basis of an exemplary compliant-mechanism, this work shows how machine learning methods can be applied to successfully learn the corresponding kinematics. This allows statements on how the actuators have to be controlled in order to reach arbitrary points with the mechanism.