Neural-Network-Based Fuzzy Observer With Data-Driven Uncertainty Identification for Vehicle Dynamics Estimation Under Extreme Driving Conditions: Theory and Experimental Results-Reference-Cited by-同舟云学术

Neural-Network-Based Fuzzy Observer With Data-Driven Uncertainty Identification for Vehicle Dynamics Estimation Under Extreme Driving Conditions: Theory and Experimental Results

Published:2023-07 Issue:7 Volume:72 Page:8686-8696
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Nguyen Cuong M.¹^ORCID,Nguyen Anh-Tu¹^ORCID,Delprat Sébastien¹^ORCID

Affiliation:

1. Laboratory LAMIH UMR CNRS 8201, Université Polytechnique Hauts-de-France, Valenciennes, France

Funder

European Regional Development Fund

State, and the Hauts-de-France Region

ANR HM-Science

Regional Delegation for Research and Technology

Ministry of Higher Education and Research

French National Center for Scientific Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/10186246/10054430.pdf?arnumber=10054430

Reference45 articles.

1. Opinion Dynamics-Based Vehicle Velocity Estimation and Diagnosis

2. Sideslip angle estimator based on ANFIS for vehicle handling and stability

3. Vehicle Sideslip Angle and Road Friction Estimation Using Online Gradient Descent Algorithm

4. A robust observer based on H∞ filtering with parameter uncertainties combined with Neural Networks for estimation of vehicle roll angle

5. Unknown Input Observers for Simultaneous Estimation of Vehicle Dynamics and Driver Torque: Theoretical Design and Hardware Experiments

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