Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Multi-Rate Planning and Control of Uncertain Nonlinear Systems: Model Predictive Control and Control Lyapunov Functions
Modern control systems must operate in increasingly complex environments subject to safety constraints and input limits, and are often implemented in a hierarchical fashion with different controllers running at multiple …
Model Predictive ControlMachine Learning Integrated with Model Predictive Control for Imitative Optimal Control of Compression Ignition Engines
The high thermal efficiency and reliability of the compression-ignition engine makes it the first choice for many applications. For this to continue, a reduction of the pollutant emissions is needed. One solution is the …
Model Predictive ControlCertified machine learning: A posteriori error estimation for physics-informed neural networks
Physics-informed neural networks (PINNs) are one popular approach to incorporate a priori knowledge about physical systems into the learning framework. PINNs are known to be robust for smaller training sets, derive bette…
BIG-bench Machine LearningModel Predictive ControlFunctional Stability of Discounted Markov Decision Processes Using Economic MPC Dissipativity Theory
This paper discusses the functional stability of closed-loop Markov Chains under optimal policies resulting from a discounted optimality criterion, forming Markov Decision Processes (MDPs). We investigate the stability o…
Model Predictive ControlQ-LearningvalidModel Predictive Control for Fluid Human-to-Robot Handovers
Human-robot handover is a fundamental yet challenging task in human-robot interaction and collaboration. Recently, remarkable progressions have been made in human-to-robot handovers of unknown objects by using learning-b…
Model Predictive ControlOpen-Ended Question AnsweringDeep Learning based Model Predictive Control for Compression Ignition Engines
Machine learning (ML) and a nonlinear model predictive controller (NMPC) are used in this paper to minimize the emissions and fuel consumption of a compression ignition engine. In this work machine learning is applied in…
Deep LearningModel Predictive ControlOptimal Management of a Smart Port with Shore-Connection and Hydrogen Supplying by Stochastic Model Predictive Control
The paper proposes an optimal management strategy for a Smart Port equipped with renewable generation and composed by an electrified quay, operating Cold-Ironing, and a Hydrogen-based quay, supplying Zero-Emission Ships.…
ManagementModel Predictive ControlStochastic OptimizationData-Driven Model Predictive Control for Linear Time-Periodic Systems
We consider the problem of data-driven predictive control for an unknown discrete-time linear time-periodic (LTP) system of known period. Our proposed strategy generalizes both Data-enabled Predictive Control (DeePC) and…
LEMMAModel Predictive ControlImpact of Information Flow Topology on Safety of Tightly-coupled Connected and Automated Vehicle Platoons Utilizing Stochastic Control
Cooperative driving, enabled by Vehicle-to-Everything (V2X) communication, is expected to significantly contribute to the transportation system's safety and efficiency. Cooperative Adaptive Cruise Control (CACC), a major…
GPRModel Predictive ControlSafe Hierarchical Model Predictive Control and Planning for Autonomous Systems
Planning and control for autonomous vehicles usually are hierarchical separated. However, increasing performance demands and operating in highly dynamic environments requires an frequent re-evaluation of the planning and…
Autonomous VehiclesCollision AvoidanceModel Predictive ControlResearch on Flexibility Margin of Electric-Hydrogen Coupling Energy Block Based on Model Predictive Control
Hydrogen energy plays an important role in the transformation of low-carbon energy, and electric hydrogen coupling will become a typical energy scenario. Aiming at the operation flexibility of low-carbon electricity hydr…
Model Predictive ControlSchedulingFlexible development and evaluation of machine-learning-supported optimal control and estimation methods via HILO-MPC
Model-based optimization approaches for monitoring and control, such as model predictive control and optimal state and parameter estimation, have been used for decades in many engineering applications. Models describing …
BIG-bench Machine LearningCode GenerationModel Predictive Controlparameter estimationState and parameter estimation for retinal laser treatment
Adequate therapeutic retinal laser irradiation needs to be adapted to the local absorption. This leads to time-consuming treatments as the laser power needs to be successively adjusted to avoid under- and overtreatment c…
Model Predictive Controlparameter estimationSafe and Efficient Model Predictive Control Using Neural Networks: An Interior Point Approach
Model predictive control (MPC) provides a useful means for controlling systems with constraints, but suffers from the computational burden of repeatedly solving an optimization problem in real time. Offline (explicit) so…
Model Predictive ControlDistributionally Robust Model Predictive Control with Total Variation Distance
This paper studies the problem of distributionally robust model predictive control (MPC) using total variation distance ambiguity sets. For a discrete-time linear system with additive disturbances, we provide a condition…
Computational EfficiencyModel Predictive ControlIdentification of Friction Models for MPC-based Control of a PowerCube Serial Robot
For model-based control, an accurate and in its complexity suitable representation of the real system is a decisive prerequisite for high and robust control quality. In a structured step-by-step procedure, a model predic…
FrictionModel Predictive ControlData-driven predictive control in a stochastic setting: a unified framework
Data-driven predictive control (DDPC) has been recently proposed as an effective alternative to traditional model-predictive control (MPC) for its unique features of being time-efficient and unbiased with respect to the …
Model Predictive ControlRobust Model Predictive Control with Polytopic Model Uncertainty through System Level Synthesis
We propose a robust model predictive control (MPC) method for discrete-time linear systems with polytopic model uncertainty and additive disturbances. Optimizing over linear time-varying (LTV) state feedback controllers …
modelModel Predictive ControlA distributionally robust optimization approach to two-sided chance constrained stochastic model predictive control with unknown noise distribution
In this work, we propose a distributionally robust stochastic model predictive control (DR-SMPC) algorithm to address the problem of two-sided chance constrained discrete-time linear system corrupted by additive noise. T…
Model Predictive ControlAutonomous Wheel Loader Trajectory Tracking Control Using LPV-MPC
In this paper, we present a systematic approach for high-performance and efficient trajectory tracking control of autonomous wheel loaders. With the nonlinear dynamic model of a wheel loader, nonlinear model predictive c…
Computational EfficiencyModel Predictive ControlTrajectory Planning