189 citations · 686 across the 33 of their papers we have counts for
12 papers · 1 filter
Distributionally Robust Surrogate Optimal Control for High-Dimensional Systems
Aaron Kandel, Saehong Park, Scott Moura
This paper presents a novel methodology for tractably solving optimal control and offline reinforcement learning problems for high-dimensional systems. This work is motivated by th…
Joint Design for Electric Fleet Operator an Charging Service Provider: Understanding the Non-Cooperative Nature
Yiqi Zhao, Teng Zeng, Zaid Allybokus +2
This work proposes a new modeling framework for jointly optimizing the charging network design and the logistic mobility planning for an electric vehicle fleet. Existing literature…
Hopfield Neural Network Flow: A Geometric Viewpoint
Abhishek Halder, Kenneth F. Caluya, Bertrand Travacca +1
We provide gradient flow interpretations for the continuous-time continuous-state Hopfield neural network (HNN). The ordinary and stochastic differential equations associated with…
Reinforcement Learning versus PDE Backstepping and PI Control for Congested Freeway Traffic
Huan Yu, Saehong Park, Alexandre Bayen +2
We develop reinforcement learning (RL) boundary controllers to mitigate stop-and-go traffic congestion on a freeway segment. The traffic dynamics of the freeway segment are governe…
Solving Overstay in PEV Charging Station Planning via Chance Constrained Optimization
Teng Zeng, Hongcai Zhang, Scott Moura
Currently, the utilization rate of public plug-in electric vehicle (PEV) charging stations is only 15%. During the other 85% of the time, the chargers are either idle or occupied b…
Joint Fleet Sizing and Charging System Planning for Autonomous Electric Vehicles
Hongcai Zhang, Colin J. R. Sheppard, Timothy E. Lipman +1
This paper studies the joint fleet sizing and charging system planning problem for a company operating a fleet of autonomous electric vehicles (AEVs) for passenger and goods transp…
Cybersecurity in Distributed and Fully-Decentralized Optimization: Distortions, Noise Injection, and ADMM
Eric Munsing, Scott Moura
As problems in machine learning, smartgrid dispatch, and IoT coordination problems have grown, distributed and fully-decentralized optimization models have gained attention for pro…
Robust Optimal Eco-driving Control with Uncertain Traffic Signal Timing
Chao Sun, Xinwei Shen, Scott Moura
This paper proposes a robust optimal eco-driving control strategy considering multiple signalized intersections with uncertain traffic signal timing. A spatial vehicle velocity pro…
Robust Eco-Driving Control of Autonomous Vehicles Connected to Traffic Lights
Chao Sun, Jacopo Guanetti, Francesco Borrelli +1
This paper focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalize…
Data-driven Chance-constrained Regulation Capacity Offering for Distributed Energy Resources
Hongcai Zhang, Zechun Hu, Eric Munsing +2
This paper studies the behavior of a strategic aggregator offering regulation capacity on behalf of a group of distributed energy resources (DERs, e.g. plug-in electric vehicles) i…
Joint Planning of PEV Fast-Charging Network and Distributed PV Generation Using the Accelerated Generalized Benders Decomposition
Hongcai Zhang, Scott J. Moura, Zechun Hu +2
Integration of plug-in electric vehicles (PEVs) with distributed renewable resources will decrease PEVs' well-to-wheels greenhouse gas emissions, promote renewable power adoption a…
A Second Order Cone Programming Model for Planning PEV Fast-Charging Stations
Hongcai Zhang, Scott Moura, Zechun Hu +2
This paper studies siting and sizing of plug-in electric vehicle (PEV) fast-charging stations on coupled transportation and power networks. We develop a closed-form service rate mo…