Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Optimal Operating Strategy for PV-BESS Households: Balancing Self-Consumption and Self-Sufficiency
High penetration of Photovoltaic (PV) generation and Battery Energy Storage System (BESS) in individual households increases the demand for solutions to determine the optimal PV generation power and the capacity of BESS.…
Model Predictive ControlReinforcement Learning (RL)SchedulingAutonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
The controller is one of the most important modules in the autonomous driving pipeline, ensuring the vehicle reaches its desired position. In this work, a reinforcement learning based lateral control approach, despite th…
Autonomous DrivingDeep Reinforcement LearningModel Predictive Controlreinforcement-learning+1Update-Aware Robust Optimal Model Predictive Control for Nonlinear Systems
Robust optimal or min-max model predictive control (MPC) approaches aim to guarantee constraint satisfaction over a known, bounded uncertainty set while minimizing a worst-case performance bound. Traditionally, these met…
Model Predictive ControlHMPC-assisted Adversarial Inverse Reinforcement Learning for Smart Home Energy Management
This letter proposes an Adversarial Inverse Reinforcement Learning (AIRL)-based energy management method for a smart home, which incorporates an implicit thermal dynamics model. In the proposed method, historical optimal…
energy managementManagementModel Predictive Controlreinforcement-learning+1System Identification for Virtual Sensor-Based Model Predictive Control: Application to a 2-DoF Direct-Drive Robotic Arm
Nonlinear Model Predictive Control (NMPC) offers a powerful approach for controlling complex nonlinear systems, yet faces two key challenges. First, accurately modeling nonlinear dynamics remains difficult. Second, varia…
Model Predictive ControlPhysics-Informed Neural Network for Cross-Domain Predictive Control of Tapered Amplifier Thermal Stabilization
Thermally induced laser noise poses a critical limitation to the sensitivity of quantum sensor arrays employing ultra-stable amplified lasers, primarily stemming from nonlinear gain-temperature coupling effects in tapere…
Model Predictive ControlAlgorithmic Control Improves Residential Building Energy and EV Management when PV Capacity is High but Battery Capacity is Low
Efficient energy management in prosumer households is key to alleviating grid stress in an energy transition marked by electric vehicles (EV), renewable energies and battery storage. However, it is unclear how households…
Deep Reinforcement Learningenergy managementManagementModel Predictive ControlDeep Operator Neural Network Model Predictive Control
In this paper, we consider the design of model predictive control (MPC) algorithms based on deep operator neural networks (DeepONets). These neural networks are capable of accurately approximating real and complex valued…
modelModel Predictive ControlKnot So Simple: A Minimalistic Environment for Spatial Reasoning
We propose KnotGym, an interactive environment for complex, spatial reasoning and manipulation. KnotGym includes goal-oriented rope manipulation tasks with varying levels of complexity, all requiring acting from pure ima…
Model Predictive ControlSpatial ReasoningSampled-data Systems: Stability, Contractivity and Single-iteration Suboptimal MPC
This paper analyzes the stability of interconnected continuous-time (CT) and discrete-time (DT) systems coupled through sampling and zero-order hold mechanisms. The DT system updates its output at regular intervals $T>0$…
Model Predictive ControlGaze Into the Abyss -- Planning to Seek Entropy When Reward is Scarce
Model-based reinforcement learning (MBRL) offers an intuitive way to increase the sample efficiency of model-free RL methods by simultaneously training a world model that learns to predict the future. MBRL methods have p…
Model-based Reinforcement LearningModel Predictive ControlEfficient Configuration-Constrained Tube MPC via Variables Restriction and Template Selection
Configuration-Constrained Tube Model Predictive Control (CCTMPC) offers flexibility by using a polytopic parameterization of invariant sets and the optimization of an associated vertex control law. This flexibility, howe…
Model Predictive ControlRegularized Model Predictive Control
In model predictive control (MPC), the choice of cost-weighting matrices and designing the Hessian matrix directly affects the trade-off between rapid state regulation and minimizing the control effort. However, traditio…
modelModel Predictive ControlComparative Analysis of Black-Box Optimization Methods for Weather Intervention Design
As climate change increases the threat of weather-related disasters, research on weather control is gaining importance. The objective of weather control is to mitigate disaster risks by administering interventions with o…
Bayesian OptimizationEfficient ExplorationModel Predictive ControlControl Invariant Sets for Neural Network Dynamical Systems and Recursive Feasibility in Model Predictive Control
Neural networks are powerful tools for data-driven modeling of complex dynamical systems, enhancing predictive capability for control applications. However, their inherent nonlinearity and black-box nature challenge cont…
Autonomous DrivingModel Predictive ControlDiffusion-assisted Model Predictive Control Optimization for Power System Real-Time Operation
This paper presents a modified model predictive control (MPC) framework for real-time power system operation. The framework incorporates a diffusion model tailored for time series generation to enhance the accuracy of th…
Load ForecastingModel Predictive ControlTime SeriesTime Series GenerationIntegrating Koopman theory and Lyapunov stability for enhanced model predictive control in nonlinear systems
This paper delves into the challenges posed by the increasing complexity of modern control systems, specifically focusing on bilinear systems, a prevalent subclass of non-linear systems characterized by state dynamics in…
Model Predictive ControlFinite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
Gaussian Process (GP) regression is shown to be effective for learning unknown dynamics, enabling efficient and safety-aware control strategies across diverse applications. However, existing GP-based model predictive con…
Model Predictive ControlLeveraging Reinforcement Learning and Koopman Theory for Enhanced Model Predictive Control Performance
This study presents an innovative approach to Model Predictive Control (MPC) by leveraging the powerful combination of Koopman theory and Deep Reinforcement Learning (DRL). By transforming nonlinear dynamical systems int…
Deep Reinforcement LearningModel Predictive ControlIntegrated Localization and Path Planning for an Ocean Exploring Team of Autonomous Underwater Vehicles with Consensus Graph Model Predictive Control
Navigation of a team of autonomous underwater vehicles (AUVs) coordinated by an unmanned surface vehicle (USV) is efficient and reliable for deep ocean exploration. AUVs depart from and return to the USV after collaborat…
Model Predictive Control