Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Improved Sample Complexity of Imitation Learning for Barrier 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 LearningModel Predictive ControlEstimation of Constraint Admissible Invariant Set with Neural Lyapunov Function
Constraint admissible positively invariant (CAPI) sets play a pivotal role in ensuring safety in control and planning applications, such as the recursive feasibility guarantee of explicit reference governor and model pre…
Model Predictive ControlUnifying back-propagation and forward-forward algorithms through model predictive control
We introduce a Model Predictive Control (MPC) framework for training deep neural networks, systematically unifying the Back-Propagation (BP) and Forward-Forward (FF) algorithms. At the same time, it gives rise to a range…
Model Predictive ControlLearning-based model predictive control with moving horizon state estimation for autonomous racing
This paper addresses autonomous racing by introducing a real-time nonlinear model predictive controller (NMPC) coupled with a moving horizon estimator (MHE). The racing problem is solved by an NMPC-based off-line traject…
Autonomous RacingModel Predictive ControlState EstimationPhysics-Informed Echo State Networks for Modeling Controllable Dynamical Systems
Echo State Networks (ESNs) are recurrent neural networks usually employed for modeling nonlinear dynamic systems with relatively ease of training. By incorporating physical laws into the training of ESNs, Physics-Informe…
Model Predictive ControlTowards Event-Triggered NMPC for Efficient 6G Communications: Experimental Results and Open Problems
Networked control systems enable real-time control and coordination of distributed systems, leveraging the low latency, high reliability, and massive connectivity offered by 5G and future 6G networks. Applications includ…
Autonomous VehiclesModel Predictive ControlPath Following Model Predictive Control of a Coupled Autonomous Underwater Vehicle
The operation of an autonomous underwater vehicle (AUV) faces challenges in following predetermined waypoints due to coupled motions under environmental disturbances. To address this, a 3D path following guidance and con…
Model Predictive ControlModel-Free versus Model-Based Reinforcement Learning for Fixed-Wing UAV Attitude Control Under Varying Wind Conditions
This paper evaluates and compares the performance of model-free and model-based reinforcement learning for the attitude control of fixed-wing unmanned aerial vehicles using PID as a reference point. The comparison focuse…
modelModel-based Reinforcement LearningModel Predictive Controlreinforcement-learning+1Least Squares and Marginal Log-Likelihood Model Predictive Control using Normalizing Flows
Real-world (bio)chemical processes often exhibit stochastic dynamics with non-trivial correlations and state-dependent fluctuations. Model predictive control (MPC) often must consider these fluctuations to achieve reliab…
Model Predictive ControlThe Bayesian Separation Principle for Data-driven Control
This paper investigates the existence of a separation principle between model identification and control design in the context of model predictive control. First, we elucidate that the separation principle holds asymptot…
Model Predictive ControlIncremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators
Few-shot adaptation is an important capability for intelligent robots that perform tasks in open-world settings such as everyday environments or flexible production. In this paper, we propose a novel approach for non-pre…
Model Predictive ControlReinforcement Learning-based Model Predictive Control for Greenhouse Climate Control
Greenhouse climate control is concerned with maximizing performance in terms of crop yield and resource efficiency. One promising approach is model predictive control (MPC), which leverages a model of the system to optim…
Model Predictive ControlPredictionreinforcement-learningReinforcement Learning+1Probabilistically Robust Trajectory Planning of Multiple Aerial Agents
Current research on robust trajectory planning for autonomous agents aims to mitigate uncertainties arising from disturbances and modeling errors while ensuring guaranteed safety. Existing methods primarily utilize stoch…
Model Predictive ControlTrajectory PlanningLinear Model Predictive Control for Quadrotors with An Analytically Derived Koopman Model
This letter presents a Koopman-theoretic lifted linear parameter-varying (LPV) system with countably infinite dimensions to model the nonlinear dynamics of a quadrotor on SE(3) for facilitating control design. The LPV sy…
modelModel Predictive ControlReLU Surrogates in Mixed-Integer MPC for Irrigation Scheduling
Efficient water management in agriculture is important for mitigating the growing freshwater scarcity crisis. Mixed-integer Model Predictive Control (MPC) has emerged as an effective approach for addressing the complex s…
Computational Efficiencyglobal-optimizationModel Predictive ControlSchedulingBilevel Optimization for Real-Time Control with Application to Locomotion Gait Generation
Model Predictive Control (MPC) is a common tool for the control of nonlinear, real-world systems, such as legged robots. However, solving MPC quickly enough to enable its use in real-time is often challenging. One common…
Bilevel OptimizationModel Predictive ControlIntegrating Reinforcement Learning and Model Predictive Control with Applications to Microgrids
This work proposes an approach that integrates reinforcement learning and model predictive control (MPC) to solve finite-horizon optimal control problems in mixed-logical dynamical systems efficiently. Optimization-based…
Model Predictive Controlreinforcement-learningReinforcement LearningLearning a Terrain- and Robot-Aware Dynamics Model for Autonomous Mobile Robot Navigation
Mobile robots should be capable of planning cost-efficient paths for autonomous navigation. Typically, the terrain and robot properties are subject to variations. For instance, properties of the terrain such as friction …
Autonomous NavigationFrictionMeta-LearningModel Predictive Control+1A computational framework for optimal and Model Predictive Control of stochastic gene regulatory networks
Engineering biology requires precise control of biomolecular circuits, and Cybergenetics is the field dedicated to achieving this goal. A significant challenge in developing controllers for cellular functions is designin…
Computational EfficiencyModel Predictive ControlSafe and Stable Closed-Loop Learning for Neural-Network-Supported Model Predictive Control
Safe learning of control policies remains challenging, both in optimal control and reinforcement learning. In this article, we consider safe learning of parametrized predictive controllers that operate with incomplete in…
Bayesian OptimizationModel Predictive Control