Abstract
In this paper we present the implementation of a model predictive controller (MPC) for real-time control of a motion simulator based on a serial robot with 8 degrees of freedom. The goal of the controller is to accurately reproduce six reference signals simultaneously (the accelerations and angular velocities in the body frame of reference) taken from a simulated or real vehicle, by moving the human participant sitting inside the cabin located at the end effector. The controller computes the optimal combined motion of all axes while keeping the axis positions, velocities and accelerations within their limits. The motion of the axes is computed every 12 ms based on a prediction horizon consisting of 60 steps, spaced 48 ms apart, thus looking ahead 2.88 s. To evaluate tracking performance, we measured the acceleration and angular velocity in the cabin using an Inertial Measurement Unit (IMU) for synthetic (doublets and triangle-doublets) and realistic (recorded car and helicopter maneuvers) reference signals. We found that fastchanging acceleration inputs excite the natural frequencies of the system, leading to severe mechanical oscillations. These oscillations can be modelled by a second-order LTI system and mitigated by including this model in the controller. The use of proper algorithms and software allows the computations to be done in real-time.
Original language | English |
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Title of host publication | 2018 European Control Conference, ECC 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1529-1535 |
Number of pages | 7 |
ISBN (Electronic) | 9783952426982 |
DOIs | |
Publication status | Published - 2018 Nov 27 |
Event | 16th European Control Conference, ECC 2018 - Limassol, Cyprus Duration: 2018 Jun 12 → 2018 Jun 15 |
Publication series
Name | 2018 European Control Conference, ECC 2018 |
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Other
Other | 16th European Control Conference, ECC 2018 |
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Country/Territory | Cyprus |
City | Limassol |
Period | 18/6/12 → 18/6/15 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This research was supported by the EU via FP7-ITN-TEMPO (607 957) and H2020-ITN-AWESCO (642 682), by the German Federal Ministry for Economic Affairs and Energy (BMWi) via eco4wind and DyConPV, and by DFG via Research Unit FOR 2401.
Publisher Copyright:
© 2018 European Control Association (EUCA).
ASJC Scopus subject areas
- Control and Systems Engineering
- Control and Optimization