Search Results for author:
Found 9 papers, 1 papers with code
Communication-Efficient Decentralized Multi-Agent Reinforcement Learning for Cooperative Adaptive Cruise Control
Connected and autonomous vehicles (CAVs) promise next-gen transportation systems with enhanced safety, energy efficiency, and sustainability.
A Unified Framework for Online Data-Driven Predictive Control with Robust Safety Guarantees
Despite great successes, model predictive control (MPC) relies on an accurate dynamical model and requires high onboard computational power, impeding its wider adoption in engineering systems, especially for nonlinear real-time systems with limited computation power.
Extended Neighboring Extremal Optimal Control with State and Preview Perturbations
In this work, an extended NE (ENE) framework is developed to systematically adapt the nominal control to both state and preview perturbations.
Physics-Augmented Data-EnablEd Predictive Control for Eco-driving of Mixed Traffic Considering Diverse Human Behaviors
In this paper, we employ a data-enabled predictive control (DeePC) scheme to address the eco-driving of mixed traffic flows with diverse behaviors of human drivers.
O2RNet: Occluder-Occludee Relational Network for Robust Apple Detection in Clustered Orchard Environments
One key technology to fully enable efficient automated harvesting is accurate and robust apple detection, which is challenging due to complex orchard environments that involve varying lighting conditions and foliage/branch occlusions.
Dimension Reduction for Efficient Data-Enabled Predictive Control
In this letter, we propose a simple yet effective singular value decomposition (SVD) based strategy to reduce the optimization problem dimension in data-enabled predictive control (DeePC).
Data-Enabled Predictive Control for Fast Charging of Lithium-Ion Batteries with Constraint Handling
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 explicit battery models that are non-trivial to identify accurately.
Privacy-Preserving Data-Enabled Predictive Leading Cruise Control in Mixed Traffic
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 dynamical models.
Cloud-Assisted Nonlinear Model Predictive Control for Finite-Duration Tasks
In this paper, we propose a novel cloud-assisted model predictive control (MPC) framework in which we systematically fuse a cloud MPC that uses a high-fidelity nonlinear model but is subject to communication delays with a local MPC that exploits simplified dynamics (due to limited computation) but has timely feedback.
