Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Regression-Based Model Error Compensation for Hierarchical MPC Building Energy Management System
One of the major challenges in the development of energy management systems (EMSs) for complex buildings is accurate modeling. To address this, we propose an EMS, which combines a Model Predictive Control (MPC) approach …
energy managementManagementModel Predictive ControlregressionMulti-Object Manipulation via Object-Centric Neural Scattering Functions
Learned visual dynamics models have proven effective for robotic manipulation tasks. Yet, it remains unclear how best to represent scenes involving multi-object interactions. Current methods decompose a scene into discre…
Model Predictive ControlObjectObject Rearrangementparameter estimationIntegrating machine learning paradigms and mixed-integer model predictive control for irrigation scheduling
The agricultural sector currently faces significant challenges in water resource conservation and crop yield optimization, primarily due to concerns over freshwater scarcity. Traditional irrigation scheduling methods oft…
ManagementModel Predictive ControlSchedulingModel-based versus model-free feeding control and water quality monitoring for fish growth tracking in aquaculture systems
The high concentration level of the environmental factors, such as a high ammonia concentration and pH level, affect the water quality, affecting fish's survival and mass death. Therefore, there is a critical need to dev…
modelModel Predictive ControlQ-LearningHow to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations
We present a framework and algorithms to learn controlled dynamics models using neural stochastic differential equations (SDEs) -- SDEs whose drift and diffusion terms are both parametrized by neural networks. We constru…
Inductive BiasModel-based Reinforcement LearningModel Predictive ControlAutonomous Drifting with 3 Minutes of Data via Learned Tire Models
Near the limits of adhesion, the forces generated by a tire are nonlinear and intricately coupled. Efficient and accurate modelling in this region could improve safety, especially in emergency situations where high force…
Model Predictive ControlBackup Plan Constrained Model Predictive Control with Guaranteed Stability
This article proposes and evaluates a new safety concept called backup plan safety for path planning of autonomous vehicles under mission uncertainty using model predictive control (MPC). Backup plan safety is defined as…
Autonomous VehiclesComputational EfficiencyModel Predictive ControlModel Predictive Control for Integrated Lateral Stability
This paper studies the design of a Model Predictive Controller (MPC) for integrated lateral stability, traction/braking control, and rollover prevention of electric vehicles intended for very high speed (VHS) racing appl…
modelModel Predictive ControlAI Enhanced Control Engineering Methods
AI and machine learning based approaches are becoming ubiquitous in almost all engineering fields. Control engineering cannot escape this trend. In this paper, we explore how AI tools can be useful in control application…
Model Predictive ControlState EstimationExtended Neighboring Extremal Optimal Control with State and Preview Perturbations
Optimal control schemes have achieved remarkable performance in numerous engineering applications. However, they typically require high computational cost, which has limited their use in real-world engineering systems wi…
Model Predictive ControlOn the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control
Recent work in imitation learning has shown that having an expert controller that is both suitably smooth and stable enables stronger guarantees on the performance of the learned controller. However, constructing such sm…
Imitation LearningLearning TheoryModel Predictive ControlIQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control
Model-based reinforcement learning (RL) has shown great promise due to its sample efficiency, but still struggles with long-horizon sparse-reward tasks, especially in offline settings where the agent learns from a fixed …
D4RLModel-based Reinforcement LearningModel Predictive ControlOffline RL+2Mixed-Integer MPC Strategies for Fueling and Density Control in Fusion Tokamaks
Model predictive control (MPC) is promising for fueling and core density feedback control in nuclear fusion tokamaks, where the primary actuators, frozen hydrogen fuel pellets fired into the plasma, are discrete. Previou…
Model Predictive ControlGAN-MPC: Training Model Predictive Controllers with Parameterized Cost Functions using Demonstrations from Non-identical Experts
Model predictive control (MPC) is a popular approach for trajectory optimization in practical robotics applications. MPC policies can optimize trajectory parameters under kinodynamic and safety constraints and provide gu…
Generative Adversarial NetworkImitation LearningModel Predictive ControlStochastic Model Predictive Control with Dynamic Chance Constraints
This work introduces a stochastic model predictive control scheme for dynamic chance constraints. We consider linear discrete-time systems affected by unbounded additive stochastic disturbance. To synthesize an optimal c…
modelModel Predictive ControlStochastic OptimizationA Learning-based Nonlinear Model Predictive Controller for a Real Go-Kart based on Black-box Dynamics Modeling through Gaussian Processes
Lately, Nonlinear Model Predictive Control (NMPC)has been successfully applied to (semi-) autonomous driving problems and has proven to be a very promising technique. However, accurate control models for real vehicles co…
Autonomous DrivingGaussian ProcessesModel Predictive ControlSelf-Supervised Reinforcement Learning that Transfers using Random Features
Model-free reinforcement learning algorithms have exhibited great potential in solving single-task sequential decision-making problems with high-dimensional observations and long horizons, but are known to be hard to gen…
Decision MakingModel Predictive Controlreinforcement-learningReinforcement Learning+1Analysis and tuning of a three-term DMC
Most MPC (Model Predictive Control) algorithms used in industries and studied in the control academia use a two-term QP (quadratic programming), where the first term is the weighted norm of the output errors, and the sec…
Model Predictive ControlDeterministic policy gradient based optimal control with probabilistic constraints
This paper studies a deep deterministic policy gradient (DDPG) based actor critic (AC) reinforcement learning (RL) technique to control a linear discrete-time system with a quadratic control cost while ensuring a constra…
Model Predictive Controlreinforcement-learningReinforcement Learning (RL)Multirotor Ensemble Model Predictive Control I: Simulation Experiments
Nonlinear receding horizon model predictive control is a powerful approach to controlling nonlinear dynamical systems. However, typical approaches that use the Jacobian, adjoint, and forward-backward passes may lose fide…
modelModel Predictive Controlparameter estimation