Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Real-time Neural-MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms
Model Predictive Control (MPC) has become a popular framework in embedded control for high-performance autonomous systems. However, to achieve good control performance using MPC, an accurate dynamics model is key. To mai…
Model Predictive ControlModel predictive control and moving horizon estimation for adaptive optimal bolus feeding in high-throughput cultivation of \textit{E. coli}
We discuss the application of a nonlinear model predictive control (MPC) and a moving horizon estimation (MHE) to achieve an optimal operation of \textit{E. coli} fed-batch cultivations with intermittent bolus feeding. 2…
Model Predictive ControlA novel constraint tightening approach for robust data-driven predictive control
In this paper, we present a data-driven model predictive control (MPC) scheme that is capable of stabilizing unknown linear time-invariant systems under the influence of process disturbances. To this end, Willems' lemma …
LEMMAModel Predictive ControlReinforcement Learning for Optimal Control of a District Cooling Energy Plant
District cooling energy plants (DCEPs) consisting of chillers, cooling towers, and thermal energy storage (TES) systems consume a considerable amount of electricity. Optimizing the scheduling of the TES and chillers to t…
Model Predictive ControlQ-Learningreinforcement-learningReinforcement Learning (RL)+1Adaptive Model Predictive Control by Learning Classifiers
Stochastic model predictive control has been a successful and robust control framework for many robotics tasks where the system dynamics model is slightly inaccurate or in the presence of environment disturbances. Despit…
Bayesian OptimisationDensity Ratio EstimationmodelModel Predictive ControlMulti-step dual control for exploration and exploitation in autonomous search with convergence guarantee
Motivated by the recently proposed dual control for exploration and exploitation (DCEE) concept, this paper presents a Multi-Step DCEE (MS-DCEE) framework with guaranteed convergence for autonomous search of a source of …
Model Predictive ControlTemporal Difference Learning for Model Predictive Control
Data-driven model predictive control has two key advantages over model-free methods: a potential for improved sample efficiency through model learning, and better performance as computational budget for planning increase…
continuous-controlContinuous ControlmodelModel Predictive ControlLearning Solution Manifolds for Control Problems via Energy Minimization
A variety of control tasks such as inverse kinematics (IK), trajectory optimization (TO), and model predictive control (MPC) are commonly formulated as energy minimization problems. Numerical solutions to such problems a…
Imitation LearningModel Predictive ControlBayesian Learning Approach to Model Predictive Control
This study presents a Bayesian learning perspective towards model predictive control algorithms. High-level frameworks have been developed separately in the earlier studies on Bayesian learning and sampling-based model p…
modelModel Predictive ControlStochastic Model Predictive Control using Initial State Optimization
We propose a stochastic MPC scheme using an optimization over the initial state for the predicted trajectory. Considering linear discrete-time systems under unbounded additive stochastic disturbances subject to chance co…
Model Predictive ControlAutonomous and Resilient Control for Optimal LEO Satellite Constellation Coverage Against Space Threats
LEO satellite constellation coverage has served as the base platform for various space applications. However, the rapidly evolving security environment such as orbit debris and adversarial space threats are greatly endan…
Model Predictive ControlRecursively feasible stochastic predictive control using an interpolating initial state constraint -- extended version
We present a stochastic model predictive control (SMPC) framework for linear systems subject to possibly unbounded disturbances. State of the art SMPC approaches with closed-loop chance constraint satisfaction recursivel…
Model Predictive ControlLearning Stochastic Parametric Differentiable Predictive Control Policies
The problem of synthesizing stochastic explicit model predictive control policies is known to be quickly intractable even for systems of modest complexity when using classical control-theoretic methods. To address this c…
Computational EfficiencyModel Predictive ControlBayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty
We propose an adaptive optimisation approach for tuning stochastic model predictive control (MPC) hyper-parameters while jointly estimating probability distributions of the transition model parameters based on performanc…
Bayesian OptimisationmodelModel Predictive ControlDistributed-MPC with Data-Driven Estimation of Bus Admittance Matrix in Voltage Control
This article presents a distributed model-predictive control (MPC) design for real-time voltage control in power systems, including an online method to estimate the bus admittance matrix $\mathbf{Y}$ to let it be time-va…
Anomaly DetectionDistributed OptimizationModel Predictive ControlModel predictive control for retinal laser treatment at 1 kHz
Laser photocoagulation is a technique applied in the treatment of retinal diseases. While this is often done manually or using simple control schemes, we pursue an optimization-based approach, namely Model Predictive Con…
Model Predictive ControlState EstimationData-driven distributed MPC of dynamically coupled linear systems
In this paper, we present a data-driven distributed model predictive control (MPC) scheme to stabilise the origin of dynamically coupled discrete-time linear systems subject to decoupled input constraints. The local opti…
LEMMAModel Predictive ControlModel Predictive Control with Preview: Recursive Feasibility and Stability
This paper proposes a stabilising model predictive control (MPC) scheme with preview information of disturbance for nonlinear systems. The proposed MPC algorithm is able to not only reject disturbance by making use of di…
Model Predictive ControlParameter estimation and model reduction for retinal laser treatment
Laser photocoagulation is one of the most frequently used treatment approaches for retinal diseases such as diabetic retinopathy and macular edema. The use of model-based control, such as Model Predictive Control (MPC), …
Model Predictive Controlparameter estimationSensitivityReinforcement Learning from Demonstrations by Novel Interactive Expert and Application to Automatic Berthing Control Systems for Unmanned Surface Vessel
In this paper, two novel practical methods of Reinforcement Learning from Demonstration (RLfD) are developed and applied to automatic berthing control systems for Unmanned Surface Vessel. A new expert data generation met…
Model Predictive Controlreinforcement-learningReinforcement LearningReinforcement Learning (RL)