A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control for Systems under General Disturbances
Systems and Control
2022-07-19 v1 Systems and Control
Optimization and Control
Abstract
This paper presents a nonlinear model predictive control strategy for stochastic systems with general (state and input dependent) disturbances subject to chance constraints. Our approach uses an online computed stochastic tube to ensure stability, constraint satisfaction and recursive feasibility in the presence of stochastic uncertainties. The shape of the tube and the constraint backoff is based on an offline computed incremental Lyapunov function.
Keywords
Cite
@article{arxiv.1912.01946,
title = {A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control for Systems under General Disturbances},
author = {Henning Schlüter and Frank Allgöwer},
journal= {arXiv preprint arXiv:1912.01946},
year = {2022}
}