Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
A Lightweight Energy Management Method for Hybrid PV/Battery/Load Systems
In this paper, a computationally lightweight algorithm is introduced for hybrid PV/Battery/Load systems that is price responsive, responds fast, does not require powerful hardware, and considers the operational limitatio…
energy managementManagementModel Predictive ControlPrivacy Analysis of Affine Transformations in Cloud-based MPC: Vulnerability to Side-knowledge
Search for the optimizer in computationally demanding model predictive control (MPC) setups can be facilitated by Cloud as a service provider in cyber-physical systems. This advantage introduces the risk that Cloud can o…
FormModel Predictive ControlPrivacy PreservingSampled-Data Primal-Dual Gradient Dynamics in Model Predictive Control
Model Predictive Control (MPC) is a versatile approach capable of accommodating diverse control requirements that holds significant promise for a broad spectrum of industrial applications. Noteworthy challenges associate…
Model Predictive ControlOccupancy Prediction for Building Energy Systems with Latent Force Models
This paper presents a new approach to predict the occupancy for building energy systems (BES). A Gaussian Process (GP) is used to model the occupancy and is represented as a state space model that is equivalent to the fu…
Model Predictive ControlData-driven Nonlinear Model Reduction using Koopman Theory: Integrated Control Form and NMPC Case Study
We use Koopman theory for data-driven model reduction of nonlinear dynamical systems with controls. We propose generic model structures combining delay-coordinate encoding of measurements and full-state decoding to integ…
FormModel Predictive ControlState EstimationOnline convex optimization for robust control of constrained dynamical systems
This article investigates the problem of controlling linear time-invariant systems subject to time-varying and a priori unknown cost functions, state and input constraints, and exogenous disturbances. We combine the onli…
Model Predictive ControlRecursively Feasible Chance-constrained Model Predictive Control under Gaussian Mixture Model Uncertainty
We present a chance-constrained model predictive control (MPC) framework under Gaussian mixture model (GMM) uncertainty. Specifically, we consider the uncertainty that arises from predicting future behaviors of moving ob…
Autonomous DrivingmodelModel Predictive ControlTrajectory PredictionExploring Attack Resilience in Distributed Platoon Controllers with Model Predictive Control
The extensive use of distributed vehicle platoon controllers has resulted in several benefits for transportation systems, such as increased traffic flow, fuel efficiency, and decreased pollution. The rising reliance on i…
Model Predictive ControlTowards an Adaptable and Generalizable Optimization Engine in Decision and Control: A Meta Reinforcement Learning Approach
Sampling-based model predictive control (MPC) has found significant success in optimal control problems with non-smooth system dynamics and cost function. Many machine learning-based works proposed to improve MPC by a) l…
Decision MakingImitation LearningMeta Reinforcement LearningModel Predictive Control+2Gradient-based Planning with World Models
The enduring challenge in the field of artificial intelligence has been the control of systems to achieve desired behaviours. While for systems governed by straightforward dynamics equations, methods like Linear Quadrati…
Model Predictive ControlStochastic Data-Driven Predictive Control with Equivalence to Stochastic MPC
We propose a data-driven receding-horizon control method dealing with the chance-constrained output-tracking problem of unknown stochastic linear time-invariant (LTI) systems with partial state observation. The proposed …
Model Predictive ControlInformation-seeking polynomial NARX model-predictive control through expected free energy minimization
We propose an adaptive model-predictive controller that balances driving the system to a goal state and seeking system observations that are informative with respect to the parameters of a nonlinear autoregressive exogen…
Model Predictive ControlHarnessing Uncertainty for a Separation Principle in Direct Data-Driven Predictive Control
Model Predictive Control (MPC) is a powerful method for complex system regulation, but its reliance on an accurate model poses many limitations in real-world applications. Data-driven predictive control (DDPC) aims at ov…
Model Predictive ControlvalidDynGraspVS: Servoing Aided Grasping for Dynamic Environments
Visual servoing has been gaining popularity in various real-world vision-centric robotic applications. Autonomous robotic grasping often deals with unseen and unstructured environments, and in this task, Visual Servoing …
Model Predictive ControlRobotic GraspingMulti-Agent Probabilistic Ensembles with Trajectory Sampling for Connected Autonomous Vehicles
Autonomous Vehicles (AVs) have attracted significant attention in recent years and Reinforcement Learning (RL) has shown remarkable performance in improving the autonomy of vehicles. In that regard, the widely adopted Mo…
Autonomous VehiclesDecision MakingModel Predictive ControlReinforcement Learning (RL)Nonlinear Model Predictive Control of a Conductance-Based Neuron Model via Data-Driven Forecasting
Objective. Precise control of neural systems is essential to experimental investigations of how the brain controls behavior and holds the potential for therapeutic manipulations to correct aberrant network states. Model …
modelModel Predictive ControlAutomatic nonlinear MPC approximation with closed-loop guarantees
Safety guarantees are vital in many control applications, such as robotics. Model predictive control (MPC) provides a constructive framework for controlling safety-critical systems, but is limited by its computational co…
Model Predictive ControlApproximate Dynamic Programming based Model Predictive Control of Nonlinear systems
This paper studies the optimal control problem for discrete-time nonlinear systems and an approximate dynamic programming-based Model Predictive Control (MPC) scheme is proposed for minimizing a quadratic performance mea…
Model Predictive ControlSignatures Meet Dynamic Programming: Generalizing Bellman Equations for Trajectory Following
Path signatures have been proposed as a powerful representation of paths that efficiently captures the path's analytic and geometric characteristics, having useful algebraic properties including fast concatenation of pat…
Model Predictive ControlTime SeriesTime Series AnalysisClosed-Loop Finite-Time Analysis of Suboptimal Online Control
Suboptimal methods in optimal control arise due to a limited computational budget, unknown system dynamics, or a short prediction window among other reasons. Although these methods are ubiquitous, their transient perform…
Model Predictive Control