Papers Model Predictive Control
“Model Predictive Control” 태그가 달린 논문 1,582편 · 필터 해제
A Contraction-constrained Model Predictive Control for Nonlinear Processes using Disturbance Forecasts
Model predictive control (MPC) has become the most widely used advanced control method in process industry. In many cases, forecasts of the disturbances are available, e.g., predicted renewable power generation based on …
Model Predictive ControlNonlinear Model Predictive Control Based on Constraint-Aware Particle Filtering/Smoothing
Nonlinear model predictive control (NMPC) has gained widespread use in many applications. Its formulation traditionally involves repetitively solving a nonlinear constrained optimization problem online. In this paper, we…
Model Predictive ControlA Contraction-constrained Model Predictive Control for Multi-timescale Nonlinear Processes
Many chemical processes exhibit diverse timescale dynamics with a strong coupling between timescale sensitive variables. Model predictive control with a non-uniformly spaced optimisation horizon is an effective approach …
Model Predictive ControlPredictionLinearly discounted economic MPC without terminal conditions for periodic optimal operation
In this work, we study economic model predictive control (MPC) in situations where the optimal operating behavior is periodic. In such a setting, the performance of a standard economic MPC scheme without terminal conditi…
Model Predictive ControlRoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks
Modeling and manipulating elasto-plastic objects are essential capabilities for robots to perform complex industrial and household interaction tasks (e.g., stuffing dumplings, rolling sushi, and making pottery). However,…
Model Predictive ControlFlood Risk Mitigation and Valve Control in Stormwater Systems: State-Space Modeling, Control Algorithms, and Case Studies
The increasing access to non-expensive sensors, computing power, and more accurate forecasting of storm events provides unique opportunities to shift flood management practices from static approaches to an optimization-b…
ManagementModel Predictive ControlSynchronous Multistep Predictive Spectral Control of the Switching Distortion in DC--DC Converters
In automotive power electronics, distortion and electromagnetic interference (EMI) generated by the switching action of power semiconductors can be a significant challenge for the design of a compact, lightweight vehicle…
Model Predictive ControlModel predictive control of agro-hydrological systems based on a two-layer neural network modeling framework
Water scarcity is an urgent issue to be resolved and improving irrigation water-use efficiency through closed-loop control is essential. The complex agro-hydrological system dynamics, however, often pose challenges in cl…
Model Predictive ControlRisk-Averse Receding Horizon Motion Planning for Obstacle Avoidance using Coherent Risk Measures
This paper studies the problem of risk-averse receding horizon motion planning for agents with uncertain dynamics, in the presence of stochastic, dynamic obstacles. We propose a model predictive control (MPC) scheme that…
Model Predictive ControlMotion PlanningOn the Practical Design of Tube-Enhanced Multi-Stage Nonlinear Model Predictive Control
Tube-enhanced multi-stage nonlinear model predictive control is a robust control scheme that can handle a wide range of uncertainties with reduced conservatism and manageable computational complexity. In this paper, we e…
Model Predictive ControlBounding the difference between model predictive control and neural networks
There is a growing debate on whether the future of feedback control systems will be dominated by data-driven or model-driven approaches. Each of these two approaches has their own complimentary set of advantages and disa…
Model Predictive ControlSafe Stochastic Model Predictive Control
Combining efficient and safe control for safety-critical systems is challenging. Robust methods may be overly conservative, whereas probabilistic controllers require a trade-off between efficiency and safety. In this wor…
modelModel Predictive ControlSimultaneous Lane-Keeping and Obstacle Avoidance by Combining Model Predictive Control and Control Barrier Functions
In this work, we combine {Model Predictive Control} (MPC) and Control Barrier Function (CBF) design {methods} to create a hierarchical control law for simultaneous lane-keeping (LK) and obstacle avoidance (OA): at the lo…
Model Predictive ControlSafety in Augmented Importance Sampling: Performance Bounds for Robust MPPI
This work explores the nature of augmented importance sampling in safety-constrained model predictive control problems. When operating in a constrained environment, sampling based model predictive control and motion plan…
Model Predictive ControlMotion PlanningOnline No-regret Model-Based Meta RL for Personalized Navigation
The interaction between a vehicle navigation system and the driver of the vehicle can be formulated as a model-based reinforcement learning problem, where the navigation systems (agent) must quickly adapt to the characte…
Model-based Reinforcement LearningModel Predictive ControlOverall Complexity Certification of a Standard Branch and Bound Method for Mixed-Integer Quadratic Programming
This paper presents a method to certify the computational complexity of a standard Branch and Bound method for solving Mixed-Integer Quadratic Programming (MIQP) problems defined as instances of a multi-parametric MIQP. …
Model Predictive ControlComputationally efficient robust MPC using optimized constraint tightening
A robust model predictive control (MPC) method is presented for linear, time-invariant systems affected by bounded additive disturbances. The main contribution is the offline design of a disturbance-affine feedback gain …
Model Predictive ControlScalable tube model predictive control of uncertain linear systems using ellipsoidal sets
This work proposes a novel robust model predictive control (MPC) algorithm for linear systems affected by dynamic model uncertainty and exogenous disturbances. The uncertainty is modeled using a linear fractional perturb…
Model Predictive ControlParameter Filter-based Event-triggered Learning
Model-based algorithms are deeply rooted in modern control and systems theory. However, they usually come with a critical assumption - access to an accurate model of the system. In practice, models are far from perfect. …
Active LearningModel Predictive ControlSelf-triggered MPC robust to bounded packet loss via a min-max approach: extended version
Networked Control Systems typically come with a limited communication bandwidth and thus require special care when designing the underlying control and triggering law. A method that allows to consider hard constraints on…
Model Predictive Control