Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Trajectory Tracking for UAVs: An Interpolating Control Approach
Building on our previous work, this paper investigates the effectiveness of interpolating control (IC) for real-time trajectory tracking. Unlike prior studies that focused on trajectory tracking itself or UAV stabilizati…
Computational EfficiencyModel Predictive ControlHumidity-Aware Model Predictive Control for Residential Air Conditioning: A Field Study
Model predictive control of residential air conditioning could reduce energy costs and greenhouse gas emissions while maintaining or improving occupants' thermal comfort. However, most approaches to predictive air condit…
Model Predictive ControlModel Predictive Simulation Using Structured Graphical Models and Transformers
We propose an approach to simulating trajectories of multiple interacting agents (road users) based on transformers and probabilistic graphical models (PGMs), and apply it to the Waymo SimAgents challenge. The transforme…
Model Predictive ControlRecent advancements on MPC for tracking: periodic and harmonic formulations
The main benefit of model predictive control (MPC) is its ability to steer the system to a given reference without violating the constraints while minimizing some objective. Furthermore, a suitably designed MPC controlle…
Model Predictive ControlPerturbed Decision-Focused Learning for Modeling Strategic Energy Storage
This paper presents a novel decision-focused framework integrating the physical energy storage model into machine learning pipelines. Motivated by the model predictive control for energy storage, our end-to-end method in…
Model Predictive ControlPredictionFrequency Constrained MPC for Efficient Grid Side Operation of Wind Power Conversion Systems
Model predictive control (MPC) has proven its applicability in power conversion control with its fast dynamic response to reference changes while ensuring critical system constraints are satisfied. Even then, the computa…
Model Predictive ControlModel Predictive Control of the Neural Manifold
Neural manifolds are an attractive theoretical framework for characterizing the complex behaviors of neural populations. However, many of the tools for identifying these low-dimensional subspaces are correlational and pr…
modelModel Predictive ControlMeasured-state conditioned recursive feasibility for stochastic model predictive control
In this paper, we address the problem of designing stochastic model predictive control (MPC) schemes for linear systems affected by unbounded disturbances. The contribution of the paper is twofold. First, motivated by th…
Model Predictive ControlSafe and Non-Conservative Trajectory Planning for Autonomous Driving Handling Unanticipated Behaviors of Traffic Participants
Trajectory planning for autonomous driving is challenging because the unknown future motion of traffic participants must be accounted for, yielding large uncertainty. Stochastic Model Predictive Control (SMPC)-based plan…
Autonomous DrivingModel Predictive ControlTrajectory PlanningComputationally Efficient System Level Tube-MPC for Uncertain Systems
Tube-based model predictive control (MPC) is one of the principal robust control techniques for constrained linear systems affected by additive disturbances. While tube-based methods with online-computed tubes have been …
Model Predictive ControlPlanning with Adaptive World Models for Autonomous Driving
Motion planning is crucial for safe navigation in complex urban environments. Historically, motion planners (MPs) have been evaluated with procedurally-generated simulators like CARLA. However, such synthetic benchmarks …
Autonomous DrivingModel Predictive ControlMotion PlanningPolynomial Chaos-based Stochastic Model Predictive Control: An Overview and Future Research Directions
This article is devoted to providing a review of mathematical formulations in which Polynomial Chaos Theory (PCT) has been incorporated into stochastic model predictive control (SMPC). In the past decade, PCT has been sh…
Model Predictive ControlDifferentiable Predictive Control for Large-Scale Urban Road Networks
Transportation is a major contributor to CO2 emissions, making it essential to optimize traffic networks to reduce energy-related emissions. This paper presents a novel approach to traffic network control using Different…
Model Predictive ControlPhysics-informed machine learningLearning Nonlinear Reduced Order Models using State-Space Neural Networks with Ordered State Variance
A novel State-Space Neural Network with Ordered variance (SSNNO) is presented in which the state variables are ordered in decreasing variance. A systematic way of model order reduction with SSNNO is proposed, which leads…
Model Predictive ControlState EstimationSafety-Driven Battery Charging: A Fisher Information-guided Adaptive MPC with Real-time Parameter Identification
Lithium-ion (Li-ion) batteries are ubiquitous in modern energy storage systems, highlighting the critical need to comprehend and optimize their performance. Yet, battery models often exhibit poor parameter identifiabilit…
ManagementModel Predictive Controlparameter estimationReserve Provision from Electric Vehicles: Aggregate Boundaries and Stochastic Model Predictive Control
Controlled charging of electric vehicles, EVs, is a major potential source of flexibility to facilitate the integration of variable renewable energy and reduce the need for stationary energy storage. To offer system serv…
Model Predictive ControlModel predictive control for tracking using artificial references: Fundamentals, recent results and practical implementation
This paper provides a comprehensive tutorial on a family of Model Predictive Control (MPC) formulations, known as MPC for tracking, which are characterized by including an artificial reference as part of the decision var…
Model Predictive ControlEconomic Model Predictive Control of Water Distribution Systems with Accelerated Optimization Algorithm
Model predictive control (MPC) has emerged as an effective strategy for water distribution systems (WDSs) management. However, it is hampered by the computational burden for large-scale WDSs due to the combinatorial grow…
BlockingComputational EfficiencyManagementModel Predictive ControlAC4MPC: Actor-Critic Reinforcement Learning for Nonlinear Model Predictive Control
\Ac{MPC} and \ac{RL} are two powerful control strategies with, arguably, complementary advantages. In this work, we show how actor-critic \ac{RL} techniques can be leveraged to improve the performance of \ac{MPC}. The \a…
Model Predictive Controlreinforcement-learningReinforcement LearningAn overview of systems-theoretic guarantees in data-driven model predictive control
The development of control methods based on data has seen a surge of interest in recent years. When applying data-driven controllers in real-world applications, providing theoretical guarantees for the closed-loop system…
LEMMAModel Predictive Control