Modelling and simulation of a motion cueing algorithm using prediction and computational intelligence techniques

Chalak Qazani, Mohammadreza 2020, Modelling and simulation of a motion cueing algorithm using prediction and computational intelligence techniques, Ph.D. thesis, Institute for Intelligent Systems research and Innovation, Deakin University.

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Title Modelling and simulation of a motion cueing algorithm using prediction and computational intelligence techniques
Author Chalak Qazani, Mohammadreza
Institution Deakin University
School Institute for Intelligent Systems research and Innovation
Degree type Research doctorate
Degree name Ph.D.
Thesis advisor Asadi, HoushyarORCID iD for Asadi, Houshyar orcid.org/0000-0002-3620-8693
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Mohamed, ShadyORCID iD for Mohamed, Shady orcid.org/0000-0002-8851-1635
Nahavandi, DariusORCID iD for Nahavandi, Darius orcid.org/0000-0002-5007-9584
Date submitted 2020-10
Summary 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.
Language eng
Indigenous content off
Description of original 312 p.
Restricted until 2026-03-19
Copyright notice ┬ęThe author
Persistent URL http://hdl.handle.net/10536/DRO/DU:30149501

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