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A New Gantry-Tau-Based Mechanism Using Spherical Wrist and Model Predictive Control-Based Motion Cueing Algorithm

Published online by Cambridge University Press:  31 October 2019

Mohammad Reza Chalak Qazani Open the ORCID record for Mohammad Reza Chalak Qazani [Opens in a new window] ,
Houshyar Asadi  and
Saeid Nahavandi
Mohammad Reza Chalak Qazani*
Affiliation:
Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds Campus, Geelong, Victoria 3217, Australia. E-mails: houshyar.asadi@deakin.edu.au, saeid.nahavandi@deakin.edu.au
Houshyar Asadi
Affiliation:
Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds Campus, Geelong, Victoria 3217, Australia. E-mails: houshyar.asadi@deakin.edu.au, saeid.nahavandi@deakin.edu.au
Saeid Nahavandi
Affiliation:
Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds Campus, Geelong, Victoria 3217, Australia. E-mails: houshyar.asadi@deakin.edu.au, saeid.nahavandi@deakin.edu.au
*
*Corresponding author. E-mail: m.r.chalakqazani@gmail.com
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Summary

The 3 degree-of-freedom Gantry-Tau manipulator with the addition of the spherical wrist mechanism which is called Gantry-Tau-3R is designed as a high-G simulation-based motion platform (SBMP) with the capability of generating the large linear and angular displacement. The combination of both parallel and serial manipulator in newly designed Gantry-Tau-3R mechanism improves the ability of the mechanism to regenerate larger motion signals with higher linear acceleration and angular velocity. The high-frequency signals are reproduced using the parallel part of the mechanism, and sustainable low-frequency accelerations are regenerated via the serial part due to the larger rotational motion capability, which will be used through motion cueing algorithm tilt coordination channel. The proportional integral derivative (PID) and fuzzy incremental controller (FIC) are developed for the proposed mechanism to show the high path tracking performance as a motion platform. FIC reduces the motion tracking error of the newly designed Gantry-Tau-3R and increases the motion fidelity for the users of the proposed SBMP. The proposed method is implemented using Matlab/Simulink software. Finally, the results demonstrate the accurate motion signal generation using linear model predictive motion cues with a fuzzy controller, which is not possible using the common parallel and serial manipulators.

Keywords

Simulation-based motion platformHigh-G Gantry-Tau-3R manipulatorPID controllerFICLinear Model Predictive-based Motion Cueing Algorithm
Type
Articles
Information
Robotica , Volume 38 , Issue 8 , August 2020 , pp. 1359 - 1380
Copyright
© Cambridge University Press 2019

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