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

Research output: Research - peer-reviewJournal article – Annual report year: 2018

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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. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Original languageEnglish
JournalIFAC-PapersOnLine
Volume50
Issue number1
Pages (from-to)9833-9839
ISSN2405-8963
DOIs
StatePublished - 2017
CitationsWeb of Science® Times Cited: 0

    Research areas

  • Model predictive control, Cable robots, Vehicle simulators, Motion cueing, Control and Systems Engineering
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