Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Comparison of artificial neural network adaptive control techniques for a nonlinear system with delay
This research paper compares two neural-network-based adaptive controllers, namely the Hybrid Deep Learning Neural Network Controller (HDLNNC) and the Adaptive Model Predictive Control with Nonlinear Prediction and Linea…
Model Predictive ControlObjectA hierarchical adaptive nonlinear model predictive control approach for maximizing tire force usage in autonomous vehicles
The ability to reliably maximize tire force usage would improve the safety of autonomous vehicles, especially in challenging edge cases. However, vehicle control near the limits of handling has many challenges, including…
Autonomous VehiclesComputational EfficiencyFrictionModel Predictive ControlExact Worst-Case Execution-Time Analysis for Implicit Model Predictive Control
We propose the first method that determines the exact worst-case execution time (WCET) for implicit linear model predictive control (MPC). Such WCET bounds are imperative when MPC is used in real time to control safety-c…
Model Predictive ControlDevelopment and Evaluation of an Online Home Energy Management Strategy for Load Coordination in Smart Homes with Renewable Energy Sources
In this paper, a real time implementable load coordination strategy is developed for the optimization of electric demands in a smart home. The strategy minimizes the electricity cost to the home owner, while limiting the…
energy managementManagementModel Predictive ControlUnmatched uncertainty mitigation through neural network supported model predictive control
This paper presents a deep learning based model predictive control (MPC) algorithm for systems with unmatched and bounded state-action dependent uncertainties of unknown structure. We utilize a deep neural network (DNN) …
Model Predictive ControlFilter-Aware Model-Predictive Control
Partially-observable problems pose a trade-off between reducing costs and gathering information. They can be solved optimally by planning in belief space, but that is often prohibitively expensive. Model-predictive contr…
modelModel Predictive ControlVisual NavigationApproximate non-linear model predictive control with safety-augmented neural networks
Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems, but requires computationally expensive online optimization. This paper studies approximations of such MPC contr…
Model Predictive ControlDistributed Search Planning in 3-D Environments With a Dynamically Varying Number of Agents
In this work, a novel distributed search-planning framework is proposed, where a dynamically varying team of autonomous agents cooperate in order to search multiple objects of interest in three-dimension (3-D). It is ass…
Model Predictive ControlError bounds for maxout neural network approximations of model predictive control
Neural network (NN) approximations of model predictive control (MPC) are a versatile approach if the online solution of the underlying optimal control problem (OCP) is too demanding and if an exact computation of the exp…
Model Predictive ControlTreeC: a method to generate interpretable energy management systems using a metaheuristic algorithm
Energy management systems (EMS) have traditionally been implemented using rule-based control (RBC) and model predictive control (MPC) methods. However, recent research has explored the use of reinforcement learning (RL) …
energy managementManagementModel Predictive ControlReinforcement Learning (RL)Model Predictive Control with Self-supervised Representation Learning
Over the last few years, we have not seen any major developments in model-free or model-based learning methods that would make one obsolete relative to the other. In most cases, the used technique is heavily dependent on…
Computational EfficiencymodelModel Predictive ControlRepresentation LearningStochastic Model Predictive Control using Initial State and Variance Interpolation
We present a Stochastic Model Predictive Control (SMPC) framework for linear systems subject to Gaussian disturbances. In order to avoid feasibility issues, we employ a recent initialization strategy, optimizing over an …
Model Predictive ControlReachability Analysis Using Hybrid Zonotopes and Functional Decomposition
This paper proposes methods for reachability analysis of nonlinear systems in both open loop and closed loop with advanced controllers. The methods combine hybrid zonotopes, a construct called a state-update set, functio…
Model Predictive ControlReal-time Nonlinear Model Predictive Control using One-step Optimizations and Reachable Sets
Model predictive control allows solving complex control tasks with control and state constraints. However, an optimal control problem must be solved in real-time to predict the future system behavior, which is hardly pos…
Model Predictive ControlLearning Residual Model of Model Predictive Control via Random Forests for Autonomous Driving
One major issue in learning-based model predictive control (MPC) for autonomous driving is the contradiction between the system model's prediction accuracy and computation efficiency. The more situations a system model c…
Autonomous DrivingmodelModel Predictive ControlregressionData-driven HVAC Control Using Symbolic Regression: Design and Implementation
The large amount of data collected in buildings makes energy management smarter and more energy efficient. This study proposes a design and implementation methodology of data-driven heating, ventilation, and air conditio…
energy managementManagementModel Predictive Controlregression+2Distributed Model Predictive Control for Periodic Cooperation of Multi-Agent Systems
We consider multi-agent systems with heterogeneous, nonlinear agents subject to individual constraints that want to achieve a periodic, dynamic cooperative control goal which can be characterised by a set and a suitable …
Model Predictive ControlLearning Stability Attention in Vision-based End-to-end Driving Policies
Modern end-to-end learning systems can learn to explicitly infer control from perception. However, it is difficult to guarantee stability and robustness for these systems since they are often exposed to unstructured, hig…
Autonomous DrivingModel Predictive ControlModel Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology
In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must …
Model Predictive ControlMoving Obstacle Collision Avoidance via Chance-Constrained MPC with CBF
Model predictive control (MPC) with control barrier functions (CBF) is a promising solution to address the moving obstacle collision avoidance (MOCA) problem. Unlike MPC with distance constraints (MPC-DC), this approach …
Collision AvoidanceModel Predictive Control