| 제목 |
시뮬레이터에서 동역학 실시간 처리를 위한 신경망 적용 |
| 분야 |
차량동역학 및 제어 |
| 언어 |
Korean |
| 저자 |
손권(부산대학교), 이동재(부산대학교), 최경현(제주대학교), 송남용(부산대학교) |
| Key Words |
Simulator(시뮬레이터), neural network(신경망), Real-time(실시간), Dynamics(동역학), Hidden layer(은닉층) |
| 초록 |
A mometum back propagation neural network is prepared to carry out real-time dynamics simulations of a passenger car. A full-car model of fifteen degrees of freedom was constructed for vehicle dynamics analysis. Human body dynamics analysis was performed for a male driver(5O percentile Korean adult) restrained by a three point seatbelt system. The trained data using the neural network were obtained using a dynamic solver, ADAMS. The neural network were formed based on the dynamics of the simulator. The optimized hidden layer was obtained by selecting the optimal number of hidden layers. The driving scenario including bump passing and lane changing has been used for the estimation of the preposed neural network. A comparison between the trained data and neural network outputs is found to be satisfactory to show the applicability of the suggested approach. |
| 원문(PDF) |
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