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Conference Paper

Nonlinear Model Predictive Control of a Cable-Robot-Based Motion Simulator

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Katliar,  M
Project group: Motion Perception & Simulation, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84255

Teufel,  H
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Motion Perception & Simulation, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83839

Bülthoff,  HH
Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Katliar, M., Fischer, J., Frison, G., Diehl, M., Teufel, H., & Bülthoff, H. (2017). Nonlinear Model Predictive Control of a Cable-Robot-Based Motion Simulator. IFAC-PapersOnLine, 50(1), 9833-9839.


Cite as: https://hdl.handle.net/21.11116/0000-0000-C3A9-5
Abstract
In this paper we present the implementation of a model-predictive controller (MPC) for real-time control of a cable-robot-based motion simulator. The controller computes control inputs such that a desired acceleration and angular velocity at a defined point in simulator’s cabin are tracked while satisfying constraints imposed by working space and allowed cable forces of the robot. In order to fully use the simulator capabilities, we propose an approach that includes the motion platform actuation in the MPC model. The tracking performance and computation time of the algorithm are investigated in computer simulations. Furthermore, for motion simulation scenarios where the reference trajectories are not known beforehand, we derive an estimate on how much motion simulation fidelity can maximally be improved by any reference prediction scheme compared to the case when no prediction scheme is applied.