Chalak Qazani, Mohamad Reza, Asadi, Houshyar, Mohamed, Shady, Lim, Chee Peng, and Nahavandi, Saeid (2022) An optimal washout filter for motion platform using neural network and fuzzy logic. Engineering Applications of Artificial Intelligence, 108. 104564.

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Abstract

To experience the motion sensation of a real vehicle through a motion simulator, a motion cueing algorithm (MCA) is required to transform the vehicle motions to the driving motion platform (DMP) while respecting the physical limitations of DMP. In this aspect, the optimal washout filter (WF) extracts the optimal motion signals including linear accelerations and angular velocities for the DMP with consideration of the human vestibular model and DMP motion states using the linear quadratic regulator (LQR) technique. The LQR technique is employed to obtain the optimal and pre-defined higher order transfer functions by solving the Riccati equation. However, the Riccati equation is solved using fixed weights, leading to an inconvenient usage of the DMP workspace. In this research, a new optimal WF model is designed and developed using a neural network (NN) and a fuzzy logic controller (FLC). The NN is introduced to solve the Riccati equation online while the FLC model is designed to extract the weighting matrices of the LQR technique. The proposed technique considers the physical DMP limitations online and reproduces accurate motion signals with a high degree of fidelity. The results demonstrate the efficiency of the developed optimal WF model as compared with those of existing optimal WF models.

Item ID:	86743
Item Type:	Article (Research - C1)
ISSN:	1873-6769
Copyright Information:	© 2021 Elsevier Ltd. All rights reserved.
Date Deposited:	19 Aug 2025 01:10
FoR Codes:	40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400706 Field robotics @ 30% 40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400705 Control engineering @ 50% 46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461199 Machine learning not elsewhere classified @ 20%
SEO Codes:	28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280110 Expanding knowledge in engineering @ 100%
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