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 language | English (US) |
|---|---|
| Title of host publication | 2023 62nd IEEE Conference on Decision and Control, CDC 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 7277-7284 |
| Number of pages | 8 |
| ISBN (Electronic) | 9798350301243 |
| DOIs | |
| State | Published - 2023 |
| Event | 62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore Duration: Dec 13 2023 → Dec 15 2023 |
Publication series
| Name | Proceedings of the IEEE Conference on Decision and Control |
|---|---|
| ISSN (Print) | 0743-1546 |
| ISSN (Electronic) | 2576-2370 |
Conference
| Conference | 62nd IEEE Conference on Decision and Control, CDC 2023 |
|---|---|
| Country/Territory | Singapore |
| City | Singapore |
| Period | 12/13/23 → 12/15/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.