Reliable Estimation of Automotive States Based on Optimized Neural Networks and Moving Horizon Estimator-Reference-Cited by-同舟云学术

Reliable Estimation of Automotive States Based on Optimized Neural Networks and Moving Horizon Estimator

Published:2023-12 Issue:6 Volume:28 Page:3238-3249
ISSN:1083-4435
Container-title:IEEE/ASME Transactions on Mechatronics
language:
Short-container-title:IEEE/ASME Trans. Mechatron.

Author:

Song Rui¹^ORCID,Fang Yongchun¹^ORCID,Huang Haoqian²^ORCID

Affiliation:

1. Tianjin Key Laboratory of Intelligent Robotics, College of Artificial Intelligence, Institute of Robotics and Automatic Information System, Nankai University, Tianjin, China

2. College of Energy and Electrical Engineering, Hohai University, Nanjing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/3516/10361845/10098260.pdf?arnumber=10098260

Reference43 articles.

1. Adaptive Scheme for the Real-Time Estimation of Tire-Road Friction Coefficient and Vehicle Velocity

2. An Adaptive Fault-Tolerant EKF for Vehicle State Estimation With Partial Missing Measurements

3. Adaptive EKF-Based Vehicle State Estimation With Online Assessment of Local Observability

4. Simultaneous estimation of tire side-slip angle and lateral tire force for vehicle lateral stability control

5. Dimensionless Model-Based System Tracking Via Augmented Kalman Filter for Multiscale Unmanned Ground Vehicles

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