Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Safe Beyond the Horizon: Efficient Sampling-based MPC with Neural Control Barrier Functions
A common problem when using model predictive control (MPC) in practice is the satisfaction of safety specifications beyond the prediction horizon. While theoretical works have shown that safety can be guaranteed by enfor…
CPUModel Predictive ControlVariational InferenceHierarchical RL-MPC for Demand Response Scheduling
This paper presents a hierarchical framework for demand response optimization in air separation units (ASUs) that combines reinforcement learning (RL) with linear model predictive control (LMPC). We investigate two contr…
Model Predictive ControlReinforcement Learning (RL)SchedulingEmpirical Study of Dynamic Regret in Online Model Predictive Control for Linear Time-Varying Systems
Model Predictive Control (MPC) is a widely used technique for managing timevarying systems, supported by extensive theoretical analysis. While theoretical studies employing dynamic regret frameworks have established robu…
Model Predictive ControlPredictionComprehensive Review on the Control of Heat Pumps for Energy Flexibility in Distribution Networks
Decarbonization plans promote the transition to heat pumps (HPs), creating new opportunities for their energy flexibility in demand response programs, solar photovoltaic integration and optimization of distribution netwo…
Model Predictive ControlReinforcement Learning (RL)SchedulingNetwork-Realized Model Predictive Control Part II: Distributed Constraint Management
A two-layer control architecture is proposed, which promotes scalable implementations for model predictive controllers. The top layer acts as both reference governor for the bottom layer, and as a feedback controller for…
ManagementModel Predictive ControlNetwork-Realized Model Predictive Control Part I: NRF-Enabled Closed-loop Decomposition
A two-layer control architecture is proposed, which promotes scalable implementations for model predictive controllers. The top layer acts as both reference governor for the bottom layer, and as a feedback controller for…
Model Predictive ControlRobot Deformable Object Manipulation via NMPC-generated Demonstrations in Deep Reinforcement Learning
In this work, we conducted research on deformable object manipulation by robots based on demonstration-enhanced reinforcement learning (RL). To improve the learning efficiency of RL, we enhanced the utilization of demons…
Deep Reinforcement LearningDeformable Object ManipulationModel Predictive ControlReinforcement Learning (RL)+1Feature Engineering Approach to Building Load Prediction: A Case Study for Commercial Building Chiller Plant Optimization in Tropical Weather
In tropical countries with high humidity, air conditioning can account for up to 60% of a building's energy use. For commercial buildings with centralized systems, the efficiency of the chiller plant is vital, and model …
ClusteringFeature EngineeringModel Predictive ControlPredictionMonoForce: Learnable Image-conditioned Physics Engine
We propose a novel model for the prediction of robot trajectories on rough offroad terrain from the onboard camera images. This model enforces the laws of classical mechanics through a physics-aware neural symbolic layer…
Model Predictive ControlTrajectory PredictionRolling Ahead Diffusion for Traffic Scene Simulation
Realistic driving simulation requires that NPCs not only mimic natural driving behaviors but also react to the behavior of other simulated agents. Recent developments in diffusion-based scenario generation focus on creat…
Computational EfficiencyModel Predictive ControlScene GenerationSafe Reinforcement Learning-based Control for Hydrogen Diesel Dual-Fuel Engines
The urgent energy transition requirements towards a sustainable future stretch across various industries and are a significant challenge facing humanity. Hydrogen promises a clean, carbon-free future, with the opportunit…
Model Predictive ControlReinforcement Learning (RL)Safe Reinforcement LearningEIQP: Execution-time-certified and Infeasibility-detecting QP Solver
Solving real-time quadratic programming (QP) is a ubiquitous task in control engineering, such as in model predictive control and control barrier function-based QP. In such real-time scenarios, certifying that the employ…
C++ codeModel Predictive ControlA view on learning robust goal-conditioned value functions: Interplay between RL and MPC
Reinforcement learning (RL) and model predictive control (MPC) offer a wealth of distinct approaches for automatic decision-making. Given the impact both fields have had independently across numerous domains, there is gr…
Model Predictive ControlReinforcement Learning (RL)Stochastic MPC with Online-optimized Policies and Closed-loop Guarantees
This paper proposes a stochastic model predictive control method for linear systems affected by additive Gaussian disturbances. Closed-loop satisfaction of probabilistic constraints and recursive feasibility of the under…
Model Predictive ControlMachine learning-based hybrid dynamic modeling and economic predictive control of carbon capture process for ship decarbonization
Implementing carbon capture technology on-board ships holds promise as a solution to facilitate the reduction of carbon intensity in international shipping, as mandated by the International Maritime Organization. In this…
Model Predictive ControlDistributionally Robust Model Predictive Control with Mixture of Gaussian Processes
Despite the success of Gaussian process based Model Predictive Control (MPC) in robotic control, its applicability scope is greatly hindered by multimodal disturbances that are prevalent in real-world settings. Here we p…
Gaussian ProcessesModel Predictive ControlOutput-Feedback Full-State Targeting Model Predictive Control for Station-Keeping on Near-Rectilinear Halo Orbits
We develop a model predictive control (MPC) policy for station-keeping (SK) on a Near-Rectilinear Halo Orbit (NRHO). The proposed policy achieves full-state tracking of a reference NRHO via a two-maneuver control horizon…
Model Predictive ControlDynamic Incentive Selection for Hierarchical Convex Model Predictive Control
In this paper, we discuss incentive design for hierarchical model predictive control (MPC) systems viewed as Stackelberg games. We consider a hierarchical MPC formulation where, given a lower-level convex MPC (LoMPC), th…
Model Predictive ControlA Neural Network-based Multi-timestep Command Governor for Nonlinear Systems with Constraints
The multi-timestep command governor (MCG) is an add-on algorithm that enforces constraints by modifying, at each timestep, the reference command to a pre-stabilized control system. The MCG can be interpreted as a Model-P…
Model Predictive ControlAdaptive Output Feedback MPC with Guaranteed Stability and Robustness
This work proposes an adaptive output feedback model predictive control (MPC) framework for uncertain systems subject to external disturbances. In the absence of exact knowledge about the plant parameters and complete st…
Model Predictive ControlState Estimation