Future reference prediction in model predictive control based driving simulators Mohammadi, Arash, Asadi, Houshyar, Mohamed, Shady, Nelson, Kyle and Nahavandi, Saeid 2016, Future reference prediction in model predictive control based driving simulators, in ACRA 2016 : Proceedings of the ARAA Australian Conference on Robotics and Automation, Australian Robotics and Automation Association, Brisbane, Qld.. Attached Files Name Description MIMEType Size Downloads Title Future reference prediction in model predictive control based driving simulators Author(s) Mohammadi, Arash orcid.org/0000-0001-7634-8212 Asadi, Houshyar orcid.org/0000-0002-3620-8693 Mohamed, Shady orcid.org/0000-0002-8851-1635 Nelson, Kyle orcid.org/0000-0003-1956-5493 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name Australian Conference on Robotics and Automation (2016 : Brisbane, Qld.) Conference location Brisbane, Qld. Conference dates 5-6 Dec 2016 Title of proceedings ACRA 2016 : Proceedings of the ARAA Australian Conference on Robotics and Automation Publication date 2016 Total pages 8 Publisher Australian Robotics and Automation Association Place of publication Brisbane, Qld. Summary The goal of a driving simulator is to produce an environment for a driver similar to the real driving scenario. Motion cueing algorithms are used to produce a realistic motion while respecting the workspace limitations and motion simulator boundaries. Model Predictive Control has become popular recently for motion cueing. However, in this control method, the optimization is based on a predefined constant future input trajectory while it is not a practical assumption. In this research, a method is proposed to predict the future reference based on the finite history of input. This method does not require the position trajectory to follow a specific road. Simulation results show the effectiveness of the proposed model predictive control method in terms of realistic motion sensation for a driver. Language eng Field of Research 099999 Engineering not elsewhere classified Socio Economic Objective 0 Not Applicable HERDC Research category E1 Full written paper - refereed ERA Research output type E Conference publication Copyright notice ©2016, ACRA Persistent URL http://hdl.handle.net/10536/DRO/DU:30090974 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research Related Links Link Description Connect to conference website Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 01 Feb 2017, 10:38:06 EST Wed, 01 Feb 2017, 10:39:09 EST Thu, 02 Feb 2017, 04:00:58 EST Mon, 20 Mar 2017, 14:17:19 EST Tue, 21 Mar 2017, 05:30:12 EST Mon, 10 Apr 2017, 14:08:01 EST Mon, 10 Apr 2017, 14:15:01 EST Mon, 10 Apr 2017, 14:17:41 EST Tue, 08 May 2018, 12:08:19 EST Sat, 11 Aug 2018, 02:31:44 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 17 times in Scopus Search Google Scholar Access Statistics: 481 Abstract Views, 9 File Downloads  -  Detailed Statistics Created: Mon, 20 Mar 2017, 14:17:19 EST

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