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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/17368

Title: Model predictive driving simulator motion cueing algorithm with actuator-based constraints
Authors: Garrett, Nikhil J.I.
Best, Matt C.
Keywords: Driving simulator
Optimal control
Model-based control
Driver behaviour
Issue Date: 2013
Publisher: © Taylor & Francis
Citation: GARRETT, N.J.I. and BEST, M.C., 2013. Model predictive driving simulator motion cueing algorithm with actuator-based constraints. Vehicle System Dynamics, 51 (8), pp. 1151 - 1172.
Abstract: The simulator motion cueing problem has been considered extensively in the literature; approaches based on linear filtering and optimal control have been presented and shown to perform reasonably well. More recently, model predictive control (MPC) has been considered as a variant of the optimal control approach; MPC is perhaps an obvious candidate for motion cueing due to its ability to deal with constraints, in this case the platform workspace boundary. This paper presents an MPC-based cueing algorithm that, unlike other algorithms, uses the actuator positions and velocities as the constraints. The result is a cueing algorithm that can make better use of the platform workspace whilst ensuring that its bounds are never exceeded. The algorithm is shown to perform well against the classical cueing algorithm and an algorithm previously proposed by the authors, both in simulation and in tests with human drivers.
Description: This is an Accepted Manuscript of an article published by Taylor & Francis in Vehicle System Dynamics on 23/04/2013, available online: http://wwww.tandfonline.com/10.1080/00423114.2013.783219
Version: Accepted for publication
DOI: 10.1080/00423114.2013.783219
URI: https://dspace.lboro.ac.uk/2134/17368
Publisher Link: http://dx.doi.org/10.1080/00423114.2013.783219
ISSN: 0042-3114
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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