Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
Training Efficient Controllers via Analytic Policy Gradient
Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve gr…
Model Predictive ControlReinforcement Learning (RL)Robust adaptive MPC using control contraction metrics
We present a robust adaptive model predictive control (MPC) framework for nonlinear continuous-time systems with bounded parametric uncertainty and additive disturbance. We utilize general control contraction metrics (CC…
Model Predictive ControlRobust Model Predictive Control of Time-Delay Systems through System Level Synthesis
We present a robust model predictive control method (MPC) for discrete-time linear time-delayed systems with state and control input constraints. The system is subject to both polytopic model uncertainty and additive dis…
Model Predictive ControlLearning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
Despite decades of research, existing navigation systems still face real-world challenges when deployed in the wild, e.g., in cluttered home environments or in human-occupied public spaces. To address this, we present a …
Imitation LearningModel Predictive ControlConvex Model Predictive Control for Down-regulation Strategies in Wind Turbines
Wind turbine (WT) controllers are often geared towards maximum power extraction, while suitable operating constraints should be guaranteed such that WT components are protected from failures. Control strategies can be al…
Model Predictive ControlLearning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories
Data-driven models for nonlinear dynamical systems based on approximating the underlying Koopman operator or generator have proven to be successful tools for forecasting, feature learning, state estimation, and control. …
Model Predictive ControlState EstimationRAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed Neural Network
Model Predictive Control (MPC) is a state-of-the-art (SOTA) control technique which requires solving hard constrained optimization problems iteratively. For uncertain dynamics, analytical model based robust MPC imposes a…
Model Predictive ControlregressionAdaptive Output Feedback Model Predictive Control
Model predictive control (MPC) for uncertain systems in the presence of hard constraints on state and input is a non-trivial problem, and the challenge is increased manyfold in the absence of state measurements. In this …
modelModel Predictive ControlState EstimationA Robust Distributed Model Predictive Control Framework for Consensus of Multi-Agent Systems with Input Constraints and Varying Delays
This paper studies the consensus problem of general linear discrete-time multi-agent systems (MAS) with input constraints and bounded time-varying communication delays. We propose a robust distributed model predictive co…
Model Predictive ControlGesture2Path: Imitation Learning for Gesture-aware Navigation
As robots increasingly enter human-centered environments, they must not only be able to navigate safely around humans, but also adhere to complex social norms. Humans often rely on non-verbal communication through gestur…
Imitation LearningModel Predictive ControlNavigateSocial NavigationAn Edge Architecture Oriented Model Predictive Control Scheme for an Autonomous UAV Mission
In this article the implementation of a controller and specifically of a Model Predictive Controller (MPC) on an Edge Computing device, for controlling the trajectory of an Unmanned Aerial Vehicle (UAV) model, is examine…
Cloud ComputingEdge-computingFuture predictionModel Predictive ControlCase Studies for Computing Density of Reachable States for Safe Autonomous Motion Planning
Density of the reachable states can help understand the risk of safety-critical systems, especially in situations when worst-case reachability is too conservative. Recent work provides a data-driven approach to compute t…
Autonomous DrivingDensity EstimationModel Predictive ControlMotion PlanningDesigning the Model Predictive Control for Interval Type-2 Fuzzy T-S Systems Involving Unknown Time-Varying Delay in Both States and Input Vector
In this paper, the model predictive control is designed for an interval type-2 Takagi-Sugeno (T-S) system with unknown time-varying delay in state and input vectors. The time-varying delay is a weird phenomenon that is a…
Model Predictive ControlHourly operation of a regulated lake via Model Predictive Control
The optimal operation of regulated lakes is a challenging task involving conflicting objectives, ranging from controlling lake levels to avoid floods and low levels to water supply downstream. The traditional approach to…
Model Predictive ControlvalidA novel learning-based robust model predictive control energy management strategy for fuel cell electric vehicles
The multi-source electromechanical coupling makes the energy management of fuel cell electric vehicles (FCEVs) relatively nonlinear and complex especially in the types of 4-wheel-drive (4WD) FCEVs. Accurate state observi…
energy managementManagementModel Predictive ControlMultiple Control Barrier Functions: An Application to Reactive Obstacle Avoidance for a Multi-steering Tractor-trailer System
Control barrier functions (CBFs) recently introduced a systematic way to guarantee the system's safety through set invariance. Together with a nominal control method, it establishes a safety-critical control mechanism. T…
Model Predictive ControlPhysics-based Digital Twins for Autonomous Thermal Food Processing: Efficient, Non-intrusive Reduced-order Modeling
One possible way of making thermal processing controllable is to gather real-time information on the product's current state. Often, sensory equipment cannot capture all relevant information easily or at all. Digital Twi…
Experimental DesignModel Predictive ControlReal-to-Sim: Predicting Residual Errors of Robotic Systems with Sparse Data using a Learning-based Unscented Kalman Filter
Achieving highly accurate dynamic or simulator models that are close to the real robot can facilitate model-based controls (e.g., model predictive control or linear-quadradic regulators), model-based trajectory planning …
Model Predictive ControlTrajectory PlanningA Predictive Chance Constraint Rebalancing Approach to Mobility-on-Demand Services
This paper considers the problem of supply-demand imbalances in Mobility-on-Demand (MoD) services, such as Uber or DiDi Rider. Such imbalances are due to uneven stochastic travel demand and can be prevented by proactivel…
GPRModel Predictive ControlFast Adaptive Regression-based Model Predictive Control
Model predictive control (MPC) is an optimal control method that predicts the future states of the system being controlled and estimates the optimal control inputs that drive the predicted states to the required referenc…
modelModel Predictive Controlregression