Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Model predictive eco-driving control for heavy-duty trucks using Branch and Bound optimization
Eco-driving (ED) can be used for fuel savings in existing vehicles, requiring only a few hardware modifications. For this technology to be successful in a dynamic environment, ED requires an online real-time implementabl…
Model Predictive ControlA Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees
This paper presents a learning- and scenario-based model predictive control (MPC) design approach for systems modeled in linear parameter-varying (LPV) framework. Using input-output data collected from the system, a stat…
Bayesian InferenceModel Predictive ControlUncertainty QuantificationReceding Horizon Games with Coupling Constraints for Demand-Side Management
Distributed energy storage and flexible loads are essential tools for ensuring stable and robust operation of the power grid in spite of the challenges arising from the integration of volatile renewable energy generation…
ManagementModel Predictive ControlData-Driven Linear Koopman Embedding for Networked Systems: Model-Predictive Grid Control
This paper presents a data-learned linear Koopman embedding of nonlinear networked dynamics and uses it to enable real-time model predictive emergency voltage control in a power network. The approach involves a novel dat…
DecoderModel Predictive ControlLessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning
This manuscript offers the perspective of experimentalists on a number of modern data-driven techniques: model predictive control relying on Gaussian processes, adaptive data-driven control based on behavioral theory, an…
Deep Reinforcement LearningGaussian ProcessesModel Predictive Controlreinforcement-learning+1On the Steady-State Behavior of Finite-Control-Set MPC with an Application to High-Precision Power Amplifiers
Motivated by increasing precision requirements for switched power amplifiers, this paper addresses the problem of model predictive control (MPC) design for discrete-time linear systems with a finite control set (FCS). Ty…
Model Predictive ControlA Model Predictive Control Functional Continuous Time Bayesian Network for Self-Management of Multiple Chronic Conditions
Multiple chronic conditions (MCC) are one of the biggest challenges of modern times. The evolution of MCC follows a complex stochastic process that is influenced by a variety of risk factors, ranging from pre-existing co…
ManagementModel Predictive ControlStability in data-driven MPC: an inherent robustness perspective
Data-driven model predictive control (DD-MPC) based on Willems' Fundamental Lemma has received much attention in recent years, allowing to control systems directly based on an implicit data-dependent system description. …
LEMMAModel Predictive ControlModel Predictive Control of Non-Holonomic Vehicles: Beyond Differential-Drive
Non-holonomic vehicles are of immense practical value and increasingly subject to automation. However, controlling them accurately, e.g., when parking, is known to be challenging for automatic control methods, including …
Model Predictive ControlToward smart composites: small-scale, untethered prediction and control for soft sensor/actuator systems
We present formulation and open-source tools to achieve in-material model predictive control of sensor/actuator systems using learned forward kinematics and on-device computation. Microcontroller units (MCUs) that comput…
Model Predictive ControlNeural Lyapunov Differentiable Predictive Control
We present a learning-based predictive control methodology using the differentiable programming framework with probabilistic Lyapunov-based stability guarantees. The neural Lyapunov differentiable predictive control (NLD…
Model Predictive ControlStochastic MPC with robustness to bounded parametric uncertainty
The performance of model-based control techniques strongly depends on the quality of the employed dynamics model. If strong guarantees are desired, it is therefore common to robustly treat all possible sources of uncerta…
Model Predictive ControlApproximate Dynamic Programming for Constrained Linear Systems: A Piecewise Quadratic Approximation Approach
Approximate dynamic programming (ADP) faces challenges in dealing with constraints in control problems. Model predictive control (MPC) is, in comparison, well-known for its accommodation of constraints and stability guar…
Model Predictive ControlEconomic model predictive control of integrated energy systems: A multi-time-scale framework
In this work, a composite economic model predictive control (CEMPC) is proposed for the optimal operation of a stand-alone integrated energy system (IES). Time-scale multiplicity exists in IESs dynamics is taken into acc…
Decision MakingModel Predictive ControlStatistical Modeling and Forecasting of Automatic Generation Control Signals
The performance of frequency regulating units for automatic generation control (AGC) of power systems depends on their ability to track the AGC signal accurately. In addition, representative models and advanced analysis …
Model Predictive ControlTime SeriesTime Series AnalysisInterpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems
This paper presents a novel trajectory tracker for autonomous quadrotor navigation in dynamic and complex environments. The proposed framework integrates a distributional Reinforcement Learning (RL) estimator for unknown…
Distributional Reinforcement LearningModel Predictive ControlReinforcement Learning (RL)Benefits of Feedforward for Model Predictive Airpath Control of Diesel Engines
This paper investigates options to complement a diesel engine airpath feedback controller with a feedforward. The control objective is to track the intake manifold pressure and exhaust gas recirculation (EGR) rate target…
Model Predictive ControlBridging Model-based Safety and Model-free Reinforcement Learning through System Identification of Low Dimensional Linear Models
Bridging model-based safety and model-free reinforcement learning (RL) for dynamic robots is appealing since model-based methods are able to provide formal safety guarantees, while RL-based methods are able to exploit th…
Autonomous NavigationmodelModel Predictive Controlreinforcement-learning+1Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection
We propose a Model Predictive Control (MPC) method for collision-free navigation that uses amortized variational inference to approximate the distribution of optimal control sequences by training a normalizing flow condi…
Model Predictive ControlVariational InferenceInfraRisk: An Open-Source Simulation Platform for Asset-Level Resilience Analysis in Interconnected Infrastructure Networks
Integrated simulation models are emerging as an alternative for analyzing large-scale interdependent infrastructure networks due to their modeling advantages over traditional interdependency models. This paper presents a…
Model Predictive Control