Neural network isolation of system inputs for transient modelling and control

被引：0
|
作者：
Tascillo, A
机构：
来源：
1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4 | 1997年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A neural network is used to predict the sensitivity of a complex nonlinear system such as an automobile to input variation, which will aid greatly in the effort to model the system and the effects of changes to its controllers. A blend of signal processing techniques is used to provide maximum resolution neural network inputs for various drivers, vehicles, engine technologies, transmissions, velocity traces, and operating temperatures. The neural net predicts what four different vehicle outputs will be, given a sample of driving inputs.
引用
收藏
页码：718 / 723
页数：6
相关论文
共 50 条
  • [31] Hierarchical optimization control based on transient chaos neural network for stable large scale system
    Li Xin-yu
    Kang Bo
    Lv Bing-chao
    Proceedings of 2004 Chinese Control and Decision Conference, 2004, : 425 - 427
  • [32] On advantage of fuzzy neural network modelling of nonlinear system
    Wang, Xiao
    Ren, Sicong
    Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 1998, 16 (03): : 406 - 410
  • [33] Modelling of an Electromagnetic Levitation System using a Neural Network
    Duka, Adrian-Vasile
    PROCEEDINGS OF 2010 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION, QUALITY AND TESTING, ROBOTICS (AQTR 2010), VOLS. 1-3, 2010,
  • [34] Integrated process-system modelling and control through graph neural network and reinforcement learning
    Huang, Jing
    Zhang, Jianjing
    Chang, Qing
    Gao, Robert X.
    CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2021, 70 (01) : 377 - 380
  • [35] Modelling of the Automatic Depth Control Electrohydraulic System Using RBF Neural Network and Genetic Algorithm
    Xing Zong-yi
    Qin Yong
    Pang Xue-miao
    Jia Li-min
    Zhang Yuan
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2010, 2010
  • [36] Modelling of structural response and optimization of structural control system using neural network and genetic algorithm
    Li, QS
    Liu, DK
    Leung, AYT
    Zhang, N
    Tam, CM
    Yang, LF
    STRUCTURAL DESIGN OF TALL BUILDINGS, 2000, 9 (04): : 279 - 293
  • [37] A neural network approach to transmission line modelling and fault diagnosis of a hydraulic press control system
    Bailey, S
    Watton, J
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2002, 216 (I4) : 357 - 367
  • [38] The nonlinear autoregressive network with exogenous inputs (NARX) neural network to damp power system oscillations
    Carbonera, Luis Felipe Bianchi
    Pinheiro Bernardon, Daniel
    de Castro Karnikowski, Douglas
    Alberto Farret, Felix
    INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2021, 31 (01)
  • [39] Neural network control of direct torque control system
    Liu, Guohai
    Dai, Xianzhong
    Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2001, 16 (06):
  • [40] Response of traveling waves to transient inputs in neural fields
    Kilpatrick, Zachary P.
    Ermentrout, Bard
    PHYSICAL REVIEW E, 2012, 85 (02):
12345