17 citations · 30 across the 22 of their papers we have counts for
7 papers · 1 filter
An Overtaking Trajectory Planning Framework Based on Spatio-temporal Topology and Reachable Set Analysis Ensuring Time Efficiency
Wule Mao, Zhouheng Li, Entao Sun +2
Generating overtaking trajectories in high-speed scenarios is typically addressed through hierarchical planning, which often suffers from local optima due to single initial solutio…
A Data-Driven Aggressive Autonomous Racing Framework Utilizing Local Trajectory Planning with Velocity Prediction
Zhouheng Li, Bei Zhou, Cheng Hu +2
The development of autonomous driving has boosted the research on autonomous racing. However, existing local trajectory planning methods have difficulty planning trajectories with…
Learning to Drift in Extreme Turning with Active Exploration and Gaussian Process Based MPC
Guoqiang Wu, Cheng Hu, Wangjia Weng +4
Extreme cornering in racing often leads to large sideslip angles, presenting a significant challenge for vehicle control. Conventional vehicle controllers struggle to manage this s…
Dynamic fault detection and diagnosis for alkaline water electrolyzer with variational Bayesian Sparse principal component analysis
Qi Zhang, Weihua Xu, Lei Xie +1
Electrolytic hydrogen production serves as not only a vital source of green hydrogen but also a key strategy for addressing renewable energy consumption challenges. For the safe pr…
Dynamic fault detection and diagnosis of industrial alkaline water electrolyzer process with variational Bayesian dictionary learning
Qi Zhang, Lei Xie, Weihua Xu +1
Alkaline Water Electrolysis (AWE) is one of the simplest green hydrogen production method using renewable energy. AWE system typically yields process variables that are serially co…
Nonlinear sparse variational Bayesian learning based model predictive control with application to PEMFC temperature control
Qi Zhang, Lei Wang, Weihua Xu +2
The accuracy of the underlying model predictions is crucial for the success of model predictive control (MPC) applications. If the model is unable to accurately analyze the dynamic…
Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Overview and Perspectives
Runze Lin, Junghui Chen, Lei Xie +1
In the context of Industry 4.0 and smart manufacturing, the field of process industry optimization and control is also undergoing a digital transformation. With the rise of Deep Re…