Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Self-tunable approximated explicit MPC: Heat exchanger implementation and analysis
The tunable approximated explicit model predictive control (MPC) comes with the benefits of real-time tunability without the necessity of solving the optimization problem online. This paper provides a novel self-tunable …
Model Predictive ControlMaximum Likelihood Identification of Linear Models with Integrating Disturbances for Offset-Free Control
This paper addresses the identification of models for offset-free model predictive control (MPC), where LTI models are augmented with (fictitious) uncontrollable integrating modes, called integrating disturbances. The st…
Model Predictive ControlCommonPower: A Framework for Safe Data-Driven Smart Grid Control
The growing complexity of power system management has led to an increased interest in reinforcement learning (RL). To validate their effectiveness, RL algorithms have to be evaluated across multiple case studies. Case st…
Benchmarkingenergy managementManagementModel Predictive Control+4Dropout MPC: An Ensemble Neural MPC Approach for Systems with Learned Dynamics
Neural networks are lately more and more often being used in the context of data-driven control, as an approximate model of the true system dynamics. Model Predictive Control (MPC) adopts this practise leading to neural …
Model Predictive ControlNonlinear Model Predictive Control for Preview-Based Traction Control
This study presents a nonlinear model predictive control (NMPC) formulation for preview-based traction control, which uses the information on the expected tire-road friction coefficient ahead to enhance the wheel slip co…
FrictionModel Predictive ControlSensitivityNonlinear Model Predictive Control for Enhanced Path Tracking and Autonomous Drifting through Direct Yaw Moment Control and Rear-Wheel-Steering
Path tracking (PT) controllers capable of replicating race driving techniques, such as drifting beyond the limits of handling, have the potential of enhancing active safety in critical conditions. This paper presents a n…
Model Predictive ControlModel Predictive Control and Reinforcement Learning: A Unified Framework Based on Dynamic Programming
In this paper we describe a new conceptual framework that connects approximate Dynamic Programming (DP), Model Predictive Control (MPC), and Reinforcement Learning (RL). This framework centers around two algorithms, whic…
Model Predictive ControlReinforcement Learning (RL)Sensitivity Analysis for Piecewise-Affine Approximations of Nonlinear Programs with Polytopic Constraints
Nonlinear Programs (NLPs) are prevalent in optimization-based control of nonlinear systems. Solving general NLPs is computationally expensive, necessitating the development of fast hardware or tractable suboptimal approx…
Model Predictive ControlSensitivityConvex neural network synthesis for robustness in the 1-norm
With neural networks being used to control safety-critical systems, they increasingly have to be both accurate (in the sense of matching inputs to outputs) and robust. However, these two properties are often at odds with…
Model Predictive ControlNavigateDifferentially-Private Distributed Model Predictive Control of Linear Discrete-Time Systems with Global Constraints
Distributed model predictive control (DMPC) has attracted extensive attention as it can explicitly handle system constraints and achieve optimal control in a decentralized manner. However, the deployment of DMPC strategi…
Distributed OptimizationModel Predictive ControlReinforced Model Predictive Control via Trust-Region Quasi-Newton Policy Optimization
Model predictive control can optimally deal with nonlinear systems under consideration of constraints. The control performance depends on the model accuracy and the prediction horizon. Recent advances propose to use rein…
Model Predictive Controlreinforcement-learningReinforcement LearningSocially-Aware Shared Control Navigation for Assistive Mobile Robots in the Built Environment
As the number of Persons with Disabilities (PWD), particularly those with one or more physical impairments, increases, there is an increasing demand for assistive robotic technologies that can support independent mobilit…
Autonomous NavigationModel Predictive ControlNavigateRocket Landing Control with Grid Fins and Path-following using MPC
In this project, we attempt to optimize a landing trajectory of a rocket. The goal is to minimize the total fuel consumption during the landing process using different techniques. Once the optimal and feasible trajectory…
Model Predictive ControlSafe Deep Model-Based Reinforcement Learning with Lyapunov Functions
Model-based Reinforcement Learning (MBRL) has shown many desirable properties for intelligent control tasks. However, satisfying safety and stability constraints during training and rollout remains an open question. We p…
Model-based Reinforcement LearningModel Predictive Controlreinforcement-learningReinforcement LearningAutomatic parking planning control method based on improved A* algorithm
As the trend of moving away from high-precision maps gradually emerges in the autonomous driving industry,traditional planning algorithms are gradually exposing some problems. To address the high real-time, high precisio…
Autonomous DrivingModel Predictive ControlUncertainty-Aware DRL for Autonomous Vehicle Crowd Navigation in Shared Space
Safe, socially compliant, and efficient navigation of low-speed autonomous vehicles (AVs) in pedestrian-rich environments necessitates considering pedestrians' future positions and interactions with the vehicle and other…
Autonomous VehiclesDeep Reinforcement LearningModel Predictive ControlEnergy-efficient predictive control for connected, automated driving under localization uncertainty
This paper presents a data-driven Model Predictive Control (MPC) for energy-efficient urban road driving for connected, automated vehicles. The proposed MPC aims to minimize total energy consumption by controlling the ve…
Model Predictive ControlEfficient Economic Model Predictive Control of Water Treatment Process with Learning-based Koopman Operator
Used water treatment plays a pivotal role in advancing environmental sustainability. Economic model predictive control holds the promise of enhancing the overall operational performance of the water treatment facilities.…
Computational EfficiencyModel Predictive ControlA Simulation Tool for V2G Enabled Demand Response Based on Model Predictive Control
Integrating electric vehicles (EVs) into the power grid can revolutionize energy management strategies, offering both challenges and opportunities for creating a more sustainable and resilient grid. In this context, mode…
energy managementManagementModel Predictive ControlMulti-Objective Learning Model Predictive Control
Multi-Objective Learning Model Predictive Control is a novel data-driven control scheme which improves a linear system's closed-loop performance with respect to several convex control objectives over iterations of a repe…
modelModel Predictive Control