A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control for Systems under General Disturbances

Henning Schlüter; Frank Allgöwer

doi:10.1016/j.ifacol.2020.12.518

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arXiv · 1912.01946

A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control for Systems under General Disturbances

Henning Schlüter·Frank Allgöwer

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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.

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BibTeX RIS

Henning Schlüter, Frank Allgöwer. 2019-12-04. A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control for Systems under General Disturbances. https://doi.org/10.1016/j.ifacol.2020.12.518

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