Chalak Qazani, Mohamad Reza, Asadi, Houshyar, and Nahavandi, Saeid (2021) A Motion Cueing Algorithm Based on Model Predictive Control Using Terminal Conditions in Urban Driving Scenario. IEEE Systems Journal, 15 (1). pp. 445-453.

PDF (Published Version) - Published Version Restricted to Repository staff only

Abstract

The motion cueing algorithm (MCA) is in charge of the real vehicle motion feeling regeneration for the driver of the simulation-based motion platform (SBMP) with respect to its limitations. The model predictive control (MPC) has been newly employed in developing MCAs to calculate the optimal input signals for delivering the best motion feeling to the SBMP's drivers while respecting the boundaries of the platform. The stability of the MCA based on MPC has become one of the main issues for some scenarios, such as an urban driving scenario, which involves sudden decelerations/accelerations (stop and start moving), sharp and large turn, and slalom movement. The urban driving scenario destabilizes the current MCA based on MPC and leads the undesired motion fluctuations, which create an unpleasant motion artifact for the SBMP drivers. Therefore, the displacement of the SBMP should be penalized conservatively to respect the workspace boundaries for all driving scenarios. This will make the motion conservative and can cause some motion-feeling error. In this article, the concept of terminal conditions (weights and states) are employed for the first time to design and develop a new generation of MCA based on MPC to enhance the performance of the model for different scenarios, such as the heavy-traffic scenario in the urban areas. Also, the stability of the MPC by considering the terminal conditions is investigated in the MCA domain. Then, the MCA based on MPC by considering terminal conditions is developed using the MATLAB software with a presentation of the urban motion scenario. The outcomes demonstrate the effectiveness of the designed model with a common MCA based on MPC without the consideration of the terminal conditions.

Item ID:	86752
Item Type:	Article (Research - C1)
ISSN:	1937-9234
Copyright Information:	© 2020 IEEE
Date Deposited:	18 Aug 2025 23:15
FoR Codes:	40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400705 Control engineering @ 60% 40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400706 Field robotics @ 40%
SEO Codes:	28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280110 Expanding knowledge in engineering @ 100%
	More Statistics