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Found 13 papers, 1 papers with code
Minimal Constraint Violation Probability in Model Predictive Control for Linear Systems
This is achieved by first determining a set of inputs that minimize the probability of constraint violation.
Online Constraint Tightening in Stochastic Model Predictive Control: A Regression Approach
Solving chance-constrained stochastic optimal control problems is a significant challenge in control.
Offline Uncertainty Sampling in Data-driven Stochastic MPC
In this work, we exploit an offline-sampling based strategy for the constrained data-driven predictive control of an unknown linear system subject to random measurement noise.
Safe Stochastic Model Predictive Control
In this work, we propose a safety algorithm that is compatible with any stochastic Model Predictive Control method for linear systems with additive uncertainty and polytopic constraints.
Data-driven tube-based stochastic predictive control
A powerful result from behavioral systems theory known as the fundamental lemma allows for predictive control akin to Model Predictive Control (MPC) for linear time invariant (LTI) systems with unknown dynamics purely from data.
Model Predictive Control with Models of Different Granularity and a Non-uniformly Spaced Prediction Horizon
Horizon length and model accuracy are defining factors when designing a Model Predictive Controller.
Multistage Stochastic Model Predictive Control for Urban Automated Driving
For motion optimization, we propose to use a two-stage hierarchical structure that plans the trajectory and the maneuver separately.
Collision Avoidance with Stochastic Model Predictive Control for Systems with a Twofold Uncertainty Structure
Model Predictive Control (MPC) has shown to be a successful method for many applications that require control.
(Stochastic) Model Predictive Control -- a Simulation Example
This brief introduction to Model Predictive Control specifically addresses stochastic Model Predictive Control, where probabilistic constraints are considered.
Stochastic Model Predictive Control with a Safety Guarantee for Automated Driving: Extended Version
Automated vehicles require efficient and safe planning to maneuver in uncertain environments.
Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments
Then, the probabilistic grid is transformed into a binary grid of admissible and inadmissible cells by applying a threshold, representing a risk parameter.
Minimization of Constraint Violation Probability in Model Predictive Control
We propose a novel Model Predictive Control scheme that yields a solution with minimal constraint violation probability for a norm constraint in an environment with uncertainty.
Combined Robust and Stochastic Model Predictive Control for Models of Different Granularity
We therefore propose combining RMPC on a detailed model for short-term predictions and Stochastic MPC (SMPC), with chance constraints, on a simplified model for long-term predictions.
