36 citations · 68 across the 8 of their papers we have counts for
8 papers
Safe Data-Driven Predictive Control
Amin Vahidi-Moghaddam, Kaian Chen, Kaixiang Zhang +3
In the realm of control systems, model predictive control (MPC) has exhibited remarkable potential; however, its reliance on accurate models and substantial computational resources…
A Unified Framework for Online Data-Driven Predictive Control with Robust Safety Guarantees
Amin Vahidi-Moghaddam, Kaian Chen, Kaixiang Zhang +3
Despite great successes, model predictive control (MPC) relies on an accurate dynamical model and requires high onboard computational power, impeding its wider adoption in engineer…
Data-Enabled Predictive Control for Fast Charging of Lithium-Ion Batteries with Constraint Handling
Kaixiang Zhang, Kaian Chen, Xinfan Lin +5
Fast charging of lithium-ion batteries has gained extensive research interests, but most of existing methods are either based on simple rule-based charging profiles or require expl…
Privacy-Preserving Data-Enabled Predictive Leading Cruise Control in Mixed Traffic
Kaixiang Zhang, Kaian Chen, Zhaojian Li +2
Data-driven predictive control of connected and automated vehicles (CAVs) has received increasing attention as it can achieve safe and optimal control without relying on explicit d…
Offline Reinforcement Learning for Autonomous Driving with Safety and Exploration Enhancement
Tianyu Shi, Dong Chen, Kaian Chen +1
Reinforcement learning (RL) is a powerful data-driven control method that has been largely explored in autonomous driving tasks. However, conventional RL approaches learn control p…
Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Traffic
Dong Chen, Mohammad Hajidavalloo, Zhaojian Li +4
On-ramp merging is a challenging task for autonomous vehicles (AVs), especially in mixed traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate th…
PowerNet: Multi-agent Deep Reinforcement Learning for Scalable Powergrid Control
Dong Chen, Kaian Chen. Zhaojian Li, Tianshu Chu +3
This paper develops an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. Specifically, we consider the decentralized inverter-base…
MPC-based Vibration Control and Energy Harvesting Using an Electromagnetic Vibration Absorber With Inertia Nonlinearity
Kaian Chen, Zhaojian Li, Wei-Che Tai +2
Simultaneous vibration control and energy harvesting of vehicle suspensions has attracted great research interests over the past decades. However, existing frameworks tradeoff susp…