A New Fuzzy Logic Based Adaptive Motion Cueing Algorithm Using Parallel Simulation-Based Motion Platform
| Autor: | Siamak Perdrammehr, Tobias Bellmann, Shady Mohamed, Saeid Nahavandi, Houshyar Asadi, Mohammad Reza Chalak Qazani |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Raumfahrt-Systemdynamik Kinematics Computer science Acceleration Adaptation models Vehicles 02 engineering and technology Workspace Fuzzy logic Motion (physics) 020901 industrial engineering & automation Solid modeling 0202 electrical engineering electronic engineering information engineering Intelligent systems Six degrees of freedom 020201 artificial intelligence & image processing Motion planning Joint (audio engineering) Algorithm |
| Zdroj: | FUZZ-IEEE |
| Popis: | Parallel manipulators are recently used in most motion simulation laboratories as they can easily generate six degrees of freedom motion. Recently, fuzzy logic-based adaptive motion cueing algorithms (MCAs) have been employed to reproduce the motion signals. The usage of fuzzy logic-based adaptive MCA reduces the movement sensation error between the real vehicle and the simulation-based motion platform (SBMP) user considering the end-effector limitations in Cartesian space.. In this paper, a new fuzzy logic-based adaptive MCA is introduced to generate motion signals based on the joints’ limitations and the movement sensation error between the real vehicle and the SBMP user. Considering the parallel SBMP, joint limits enhance the ability of the introduced adaptive motion cueing algorithm to generate more accurate movement feelings with high fidelity. The simulation results prove that the proposed adaptive motion cueing algorithm can effectively use the large workspace of the parallel SBMP whilst reducing the motion sensation error. |
| Databáze: | OpenAIRE |
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