Chalak Qazani, Mohamadreza (2020) Modelling and simulation of a motion cueing algorithm using prediction and computational intelligence techniques. PhD thesis, Deakin University.

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Abstract

The main research question of this PhD research is how to regenerate the realistic driving/flying motion sensation for SBMP user through developing a novel MCA by considering the nonlinearities such as the sensation shape following factor, dexterity, active and passive joints’ physical and dynamical limitations as well as inverse kinematics and dynamics model of the SBMPs using nonlinear model predictive control (MPC) based on prediction and computational intelligence techniques, such as evolutionary algorithms and neural network (NN)-based techniques, to predict the vehicle motion signals. It should be noted that the above-mentioned factors are ignored in the existing studies on MCAs, and this ignorance causes false motion cues and inefficient platform workspace usage.

Item ID:	86762
Item Type:	Thesis (PhD)
Additional Information:	Thesis embargoed, see link to awarding institution, Deakin University.
Date Deposited:	12 Mar 2026 05:26
FoR Codes:	40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400711 Simulation, modelling, and programming of mechatronics systems @ 30% 40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400705 Control engineering @ 50% 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460299 Artificial intelligence not elsewhere classified @ 20%
SEO Codes:	24 MANUFACTURING > 2404 Computer, electronic and communication equipment > 240407 Robotics @ 30% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280110 Expanding knowledge in engineering @ 60% 27 TRANSPORT > 2799 Other transport > 279999 Other transport not elsewhere classified @ 10%
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