A review of dynamic state estimation for the neighborhood system of connected vehicles
Precise vehicle state and the surrounding traffic information are essential for decision-
making and dynamic control of intelligent connected vehicles. Tremendous research efforts …
making and dynamic control of intelligent connected vehicles. Tremendous research efforts …
Multinodes interval electric vehicle day-ahead charging load forecasting based on joint adversarial generation
N Huang, Q He, J Qi, Q Hu, R Wang, G Cai… - International Journal of …, 2022 - Elsevier
The spatial–temporal distribution of electric vehicle (EV) charging load has strong
randomness and is affected by battery capacity and user behavior. In addition, the multinode …
randomness and is affected by battery capacity and user behavior. In addition, the multinode …
Robust lateral trajectory following control of unmanned vehicle based on model predictive control
This article presents a trajectory following control solution for the lateral motion of an
unmanned vehicle. The proposed solution is based on model predictive lateral control. The …
unmanned vehicle. The proposed solution is based on model predictive lateral control. The …
A background-impulse Kalman filter with non-Gaussian measurement noises
X Fan, G Wang, J Han, Y Wang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In the Kalman filter (KF), the estimated state is a linear combination of the one-step
prediction and measurement. The two combination weights depend on the prediction mean …
prediction and measurement. The two combination weights depend on the prediction mean …
Fuzzy observer-based transitional path-tracking control for autonomous vehicles
This study addresses the path-tracking control issue of autonomous vehicles (AVs) when the
GPS measurement is temporarily unavailable. In such a case, the vehicle states, location or …
GPS measurement is temporarily unavailable. In such a case, the vehicle states, location or …
PAC-Bayesian framework based drop-path method for 2D discriminative convolutional network pruning
Q Zheng, X Tian, M Yang, Y Wu, H Su - Multidimensional Systems and …, 2020 - Springer
Deep convolutional neural networks (CNNs) have demonstrated its extraordinary power on
various visual tasks like object detection and classification. However, it is still challenging to …
various visual tasks like object detection and classification. However, it is still challenging to …
Estimation of sideslip angle and tire cornering stiffness using fuzzy adaptive robust cubature Kalman filter
The accurate information of sideslip angle (SA) and tire cornering stiffness (TCS) is essential
for advanced chassis control systems. However, SA and TCS cannot be directly measured …
for advanced chassis control systems. However, SA and TCS cannot be directly measured …
A practical trajectory tracking control of autonomous vehicles using linear time-varying MPC method
With the rapid development and implementation of autonomous vehicles (AVs), the
simultaneous and accurate trajectory tracking problem for such AVs has become a popular …
simultaneous and accurate trajectory tracking problem for such AVs has become a popular …
Sparse representation convolutional autoencoder for feature learning of vibration signals and its applications in machinery fault diagnosis
M Miao, Y Sun, J Yu - IEEE Transactions on Industrial …, 2021 - ieeexplore.ieee.org
Vibration signals are widely utilized in many fields, which can reflect machine health state.
Those typical deep learning techniques cannot learn impulsive features from vibration …
Those typical deep learning techniques cannot learn impulsive features from vibration …
Efficient and fast real-world noisy image denoising by combining pyramid neural network and two-pathway unscented Kalman filter
Recently, image prior learning has emerged as an effective tool for image denoising, which
exploits prior knowledge to obtain sparse coding models and utilize them to reconstruct the …
exploits prior knowledge to obtain sparse coding models and utilize them to reconstruct the …