Abstract
Thanks to the emerging integration of algorithms and simulators, recent Driving Simulators (DS) find enormous potential in applications like advanced driver-assistance devices, analysis of driver’s behaviours, research and development of new vehicles and even for entertainment purposes. Driving simulators have been developed to reduce the cost of field studies, allow more flexible control over circumstances and measurements, and safely present hazardous conditions. The major challenge in a driving simulator is to reproduce realistic motions within hardware constraints. Motion Cueing Algorithm (MCA) guarantees a realistic motion perception in the simulator. However, the complex nature of the human perception system makes MCA implementation challenging. The present research aims to improve the performance of driving simulators by proposing and implementing the MCA algorithm as a control problem. The approach is realized using an actual vehicle model integrated with a detailed model of the human vestibular system, which accurately reproduces the driver’s perception. These perception motion signals are compared with simulated ones. A 2-DOF stabilized platform model is used to test the results from the two proposed control strategies, Proportional Integrator and Derivative (PID) and Model Predictive Control (MPC).
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Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
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Acknowledgments
Ayesha Hameed acknowledges support from the Warsaw University of Technology (WUT), grant No. 504440200007. Ali Soltani Sharif Abadi acknowledges support from WUT, grant No. 504440200003.
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Ayesha Hameed received her master’s degree in electrical engineering from COMSATS University Islamabad, Pakistan. Currently, she is a PhD student in the Institute of Automatic Control and Robotics, Faculty of Mechatronics at Warsaw University of Technology, Warsaw, Poland. Her research interest includes modelling and optimization of advanced control algorithms for robotics systems.
Ali Soltani Sharif Abadi received a bachelor’s degree in electrical engineering from Urmia University, Urmia, Iran, in 2016. He graduated with a master’s degree in control from Yazd University, Yazd, Iran, in 2019. He started his doctoral studies in October 2020 at the Warsaw University of Technology (WUT), Warsaw, Poland. He has been working as a Research Assistant (RA) at WUT from June 2022 to April 2023. He is currently a faculty member and academic teacher at the WUT, Warsaw, Poland. He was awarded the “Best Team Award” from the Faculty of Mechatronics at the Warsaw University of Technology for their research group in the 2021–2022 academic year. He has received the “IJCAS Contribution Award 2020”. Also, he was awarded as the “young author” at the “XXI Polish Control Conference 2023”. His research interests include control systems, robotic minimally invasive surgery, nonlinear control, fuzzy logic, state and disturbance observers, sliding mode control, self-tuning controllers, industrial robotics, and finite/fixed and predefined time stabilization methods.
Andrzej Ordys joined Warsaw University of Technology (WUT), as a Professor in the faculty of Mechatronics, in 2019, funded by the project “Polish Returns” of the National Agency for Academic Exchange. Immediately before coming to Poland, he held the positions of Director of Applied Research at Military Technological College (MTC) in Sultanate of Oman, Head of the School of Mechanical and Automotive Engineering and Professor of Automotive Engineering in Kingston University London, British Energy Senior Lecturer in the Industrial Control Research Centre in the Department of Electronic and Electrical Engineering at the University of Strathclyde. He has managed and contributed to research activities in numerous projects funded by the EU, national agencies (e.g., EPSRC), and industry. Prof.Ordys became a senior member of IEEE. Professor Ordys’s current research interests are real-time implementation of control algorithms, modeling, and simulation of industrial systems and mechanical systems, nonlinear predictive control, industrial control, and optimal control. He develops algorithms for benchmarking the performance of controllers and for the assessment of the system’s condition. Future research plans include resilient control with applications to power networks, automotive systems, and robotics.
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Hameed, A., Abadi, A.S.S. & Ordys, A. Model Predictive Control based Motion Cueing Algorithm for Driving Simulator. J. Syst. Sci. Syst. Eng. (2023). https://doi.org/10.1007/s11518-023-5584-6
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DOI: https://doi.org/10.1007/s11518-023-5584-6