Related papers: A MEC-Based Optimization Framework for Dynamic Ind…
This paper demonstrates the applicability of the safe model predictive control (SMPC) framework to autonomous driving scenarios, focusing on the design of adaptive cruise control (ACC) and automated lane-change systems. Building on the SMPC…
This paper proposes an eco-driving framework for electric connected vehicles (CVs) based on reinforcement learning (RL) to improve vehicle energy efficiency at signalized intersections. The vehicle agent is specified by integrating the…
A major barrier to wide adoption of Electric Vehicles (EVs) is the absence of reliable and equitable charging infrastructure. Poorly located charging stations create coverage gaps and slow down EV adoption, especially in underserved…
This paper studies optimal thermal management and charging of a battery electric vehicle driving over long distance trips. The focus is on the potential benefits of including a heat pump in the thermal management system for waste heat…
The paper proposes a novel Economic Model Predictive Control (EMPC) scheme for Autonomous Surface Vehicles (ASVs) to simultaneously address path following accuracy and energy constraints under environmental disturbances. By formulating…
The last few years have seen the massive deployment of electric buses in many existing transit networks. However, the planning and operation of an electric bus system differ from that of a bus system with conventional vehicles, and some key…
We investigate interactive trajectory planning subject to uncertainty in the decisions of surrounding agents. To control the ego-agent, we aim to first learn the decision distribution and solve a Stochastic Model Predictive Control (SMPC)…
In this paper, we present a robust distributed model predictive control (DMPC) scheme for dynamically decoupled nonlinear systems which are subject to state constraints, coupled state constraints and input constraints. In the proposed…
The rapid growth of urban populations and the increasing need for sustainable transportation solutions have prompted a shift towards electric buses in public transit systems. However, the effective management of mixed fleets consisting of…
Recently, intermittent computing (IC) has received tremendous attention due to its high potential in perpetual sensing for Internet-of-Things (IoT). By harvesting ambient energy, battery-free devices can perform sensing intermittently…
A major challenge in todays power grid is to manage the increasing load from electric vehicle (EV) charging. Demand response (DR) solutions aim to exploit flexibility therein, i.e., the ability to shift EV charging in time and thus avoid…
Effective utilization of charging station capacity plays an important role in enhancing the profitability of ride-hailing systems using electric vehicles. Existing studies assume constant energy prices and uncapacitated charging stations or…
This paper presents a robust adaptive learning Model Predictive Control (MPC) framework for linear systems with parametric uncertainties and additive disturbances performing iterative tasks. The approach refines the parameter estimates…
This paper presents an enhanced electric vehicle demand response system based on large language models, aimed at optimizing the application of vehicle-to-grid technology. By leveraging an large language models-driven multi-agent framework…
The requirement for continual improvement of idle speed control (ISC) performance is increasing due to the stringent regulation on emission and fuel economy these days. In this regard, a low-complexity offset-free explicit model predictive…
In this work, we address the problem of charging coordination between electric trucks and charging stations. The problem arises from the tension between the trucks' nontrivial charging times and the stations' limited charging facilities.…
In this paper, we propose a framework for coordinating distributed energy resources (DERs) connected to a power distribution system, the model of which is not completely known, so that they collectively provide a specified amount of active…
In control applications there is often a compromise that needs to be made with regards to the complexity and performance of the controller and the computational resources that are available. For instance, the typical hardware platform in…
In the last decade, the Internet of Things paradigm has caused an exponential increase in the number of connected devices. This trend brings the Internet closer to everyday activities and enables data collection that can be used to create…
In modern cities, the number of Electric vehicles (EV) is increasing rapidly for their low emission and better dynamic performance, leading to increasing demand for EV charging. However, due to the limited number of EV charging facilities,…