A data-driven approach to nonlinear braking control

被引:0
|
作者
Novara, Carlo [1 ]
Formentin, Simone [2 ]
Savaresi, Sergio M. [2 ]
Milanese, Mario [3 ]
机构
[1] Politecn Torino, Dipartimento Automat & Informat, I-10129 Turin, Italy
[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, Milan, Italy
[3] Modelway Srl, Turin, Italy
关键词
FEEDBACK-CONTROL; DESIGN;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In modern road vehicles, active braking control systems are crucial elements to ensure safety and lateral stability. Unfortunately, the wheel slip dynamics is highly nonlinear and the on-line estimation of the road-tire conditions is still a challenging open research problem. These facts make it difficult to devise a braking control system that is reliable in any situation without being too conservative. In this paper, we propose the Data-Driven Inversion Based Control (D-2-IBC) approach to overcome the above issues. The method relies on a two degrees of freedom architecture, with a linear controller and a nonlinear controller in parallel, both designed using only experimental data. The effectiveness of the proposed approach is shown by means of an extensive simulation campaign.
引用
收藏
页码:1453 / 1458
页数:6
相关论文
共 50 条
  • [31] A Data-Driven Approach of Takagi-Sugeno Fuzzy Control of Unknown Nonlinear Systems
    Zhang, Bin
    Shin, Yung C.
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (01): : 1 - 16
  • [32] A big data-driven predictive control approach for nonlinear processes using behaviour clusters
    Han, Shuangyu
    Yan, Yitao
    Bao, Jie
    Huang, Biao
    [J]. JOURNAL OF PROCESS CONTROL, 2024, 140
  • [33] Data-driven feedforward control design for nonlinear systems: A control-oriented system identification approach
    Bolderman, Max
    Lazar, Mircea
    Butler, Hans
    [J]. 2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC, 2023, : 4530 - 4535
  • [34] Identification for control approach to data-driven model predictive control
    Zakeri, Yadollah
    Sheikholeslam, Farid
    Haeri, Mohammad
    [J]. INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL, 2024, 18 (03) : 281 - 301
  • [35] Data-driven approach for fault detection and isolation in nonlinear system
    Kallas, Maya
    Mourot, Gilles
    Maquin, Didier
    Ragot, Jose
    [J]. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2018, 32 (11) : 1569 - 1590
  • [36] A data-driven approach to model calibration for nonlinear dynamical systems
    Greve, C. M.
    Hara, K.
    Martin, R. S.
    Eckhardt, D. Q.
    Koo, J. W.
    [J]. JOURNAL OF APPLIED PHYSICS, 2019, 125 (24)
  • [37] LFT Representation of a Class of Nonlinear Systems: A Data-Driven Approach
    Sinha, Sourav
    Muniraj, Devaprakash
    Farhood, Mazen
    [J]. 2021 EUROPEAN CONTROL CONFERENCE (ECC), 2021, : 866 - 871
  • [38] Data-driven Bayesian approach for control loop diagnosis
    Qi, Fei
    Huang, Biao
    [J]. 2008 AMERICAN CONTROL CONFERENCE, VOLS 1-12, 2008, : 3368 - 3373
  • [39] Data-Driven Nonlinear Modal Analysis: A Deep Learning Approach
    Li, Shanwu
    Yang, Yongchao
    [J]. NONLINEAR STRUCTURES & SYSTEMS, VOL 1, 2023, : 229 - 231
  • [40] On a Probabilistic Approach for Inverse Data-Driven Optimal Control
    Garrabe, Emiland
    Jesawada, Hozefa
    Del Vecchio, Carmen
    Russo, Giovanni
    [J]. 2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC, 2023, : 4411 - 4416