Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
K-BMPC: Derivative-based Koopman Bilinear Model Predictive Control for Tractor-Trailer Trajectory Tracking with Unknown Parameters
Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a…
Computational EfficiencyModel Predictive ControlReal-Time Machine-Learning-Based Optimization Using Input Convex Long Short-Term Memory Network
Neural network-based optimization and control methods, often referred to as black-box approaches, are increasingly gaining attention in energy and manufacturing systems, particularly in situations where first-principles …
Chemical ProcessComputational EfficiencyDecision MakingModel Predictive ControlLearning Predictive Safety Filter via Decomposition of Robust Invariant Set
Ensuring safety of nonlinear systems under model uncertainty and external disturbances is crucial, especially for real-world control tasks. Predictive methods such as robust model predictive control (RMPC) require solvin…
Model Predictive ControlReinforcement Learning (RL)Enhancing Control Performance through ESN-Based Model Compensation in MPC for Dynamic Systems
Deriving precise system dynamic models through traditional numerical methods is often a challenging endeavor. The performance of Model Predictive Control is heavily contingent on the accuracy of the system dynamic model.…
Model Predictive ControlA Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements
This study presents a physics-informed machine learning-based control method for nonlinear dynamic systems with highly noisy measurements. Existing data-driven control methods that use machine learning for system identif…
Model Predictive ControlPhysics-informed machine learningOut-of-Distribution-Aware Electric Vehicle Charging
We tackle the challenge of learning to charge Electric Vehicles (EVs) with Out-of-Distribution (OOD) data. Traditional scheduling algorithms typically fail to balance near-optimal average performance with worst-case guar…
Model Predictive Controlreinforcement-learningReinforcement Learning (RL)SchedulingResilient and constrained consensus against adversarial attacks: A distributed MPC framework
There has been a growing interest in realizing the resilient consensus of the multi-agent system (MAS) under cyber-attacks, which aims to achieve the consensus of normal agents (i.e., agents without attacks) in a network…
Adversarial AttackAdversarial Attack DetectionModel Predictive ControlAutomated Lane Change via Adaptive Interactive MPC: Human-in-the-Loop Experiments
This article presents a new optimal control-based interactive motion planning algorithm for an autonomous vehicle interacting with a human-driven vehicle. The ego vehicle solves a joint optimization problem for its motio…
Autonomous VehiclesModel Predictive ControlMotion PlanningR$^2$NMPC: A Real-Time Reduced Robustified Nonlinear Model Predictive Control with Ellipsoidal Uncertainty Sets for Autonomous Vehicle Motion Control
In this paper, we present a novel Reduced Robustified NMPC (R$^2$NMPC) algorithm that has the same complexity as an equivalent nominal NMPC while enhancing it with robustified constraints based on the dynamics of ellipso…
Model Predictive ControlState EstimationOn the security of randomly transformed quadratic programs for privacy-preserving cloud-based control
Control related data, such as system states and inputs or controller specifications, is often sensitive. Meanwhile, the increasing connectivity of cloud-based or networked control results in vast amounts of such data, wh…
Model Predictive ControlPrivacy PreservingDeep Neural Network based Optimal Control of Greenhouses
Automatic control of greenhouse crop production is of great interest owing to the increasing energy and labor costs. In this work, we use two-level control, where the upper level generates suitable reference trajectories…
Model Predictive ControlAdaptive Stochastic Nonlinear Model Predictive Control with Look-ahead Deep Reinforcement Learning for Autonomous Vehicle Motion Control
In this paper, we present a Deep Reinforcement Learning (RL)-driven Adaptive Stochastic Nonlinear Model Predictive Control (SNMPC) to optimize uncertainty handling, constraints robustification, feasibility, and closed-lo…
Decision MakingDeep Reinforcement LearningModel Predictive ControlReinforcement Learning (RL)Safe Collective Control under Noisy Inputs and Competing Constraints via Non-Smooth Barrier Functions
We consider the problem of safely coordinating ensembles of identical autonomous agents to conduct complex missions with conflicting safety requirements and under noisy control inputs. Using non-smooth control barrier fu…
Model Predictive ControlStochastic OptimizationModel Predictive Control of Diesel Engine Emissions Based on Neural Network Modeling
This paper addresses the control of diesel engine nitrogen oxides (NOx) and Soot emissions through the application of Model Predictive Control (MPC). The developments described in the paper are based on a high-fidelity m…
Model Predictive ControlModeling and Control of Diesel Engine Emissions using Multi-layer Neural Networks and Economic Model Predictive Control
This paper presents the results of developing a multi-layer Neural Network (NN) to represent diesel engine emissions and integrating this NN into control design. Firstly, a NN is trained and validated to simultaneously p…
Model Predictive ControlMake a Donut: Hierarchical EMD-Space Planning for Zero-Shot Deformable Manipulation with Tools
Deformable object manipulation stands as one of the most captivating yet formidable challenges in robotics. While previous techniques have predominantly relied on learning latent dynamics through demonstrations, typicall…
Deformable Object ManipulationModel Predictive ControlActive Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing
Autonomous racing creates challenging control problems, but Model Predictive Control (MPC) has made promising steps toward solving both the minimum lap-time problem and head-to-head racing. Yet, accurate models of the sy…
Autonomous RacingModel Predictive ControlregressionOptimized Pseudo-Linearization-Based Model Predictive Controller Design: Direct Data-Driven Approach
To reduce the typical time-consuming routines of plant modeling for model-based controller designs, the fictitious reference iterative tuning (FRIT) has been proposed and has proven to be effective in many applications. …
Model Predictive ControlTransfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System
Increasingly, homeowners opt for photovoltaic (PV) systems and/or battery storage to minimize their energy bills and maximize renewable energy usage. This has spurred the development of advanced control algorithms that m…
Demand Forecastingenergy managementLoad ForecastingManagement+2A Stochastic Nonlinear Model Predictive Control with an Uncertainty Propagation Horizon for Autonomous Vehicle Motion Control
Employing Stochastic Nonlinear Model Predictive Control (SNMPC) for real-time applications is challenging due to the complex task of propagating uncertainties through nonlinear systems. This difficulty becomes more prono…
Autonomous VehiclesModel Predictive ControlState Estimation