Optimal Design of Control-Lyapunov Functions by Semi-Infinite Stochastic Programming

Wentao Tang, Prodromos Daoutidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Lyapunov-based control is a common method to enforce closed-loop stability of nonlinear systems, where the choice of a control-Lyapunov function has a strong impact on the resulting performance. In this paper, we propose a generic semi-infinite stochastic programming formulation for the optimal control-Lyapunov function design problem and discuss its various specializations. Specifically, the expected performance evaluated on simulated trajectories under different scenarios is optimized subject to infinite constraints on stability and performance specifications. A stochastic proximal primal-dual algorithm is introduced to find a stationary solution of such a semi-infinite stochastic programming problem. The proposed method is illustrated by a chemical reactor case study.

Original languageEnglish (US)
Title of host publication2023 62nd IEEE Conference on Decision and Control, CDC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7277-7284
Number of pages8
ISBN (Electronic)9798350301243
DOIs
StatePublished - 2023
Externally publishedYes
Event62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore
Duration: Dec 13 2023Dec 15 2023

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference62nd IEEE Conference on Decision and Control, CDC 2023
Country/TerritorySingapore
CitySingapore
Period12/13/2312/15/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

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