Report
Data-driven input-to-state stabilization with respect to measurement errors
| العنوان: | Data-driven input-to-state stabilization with respect to measurement errors |
|---|---|
| المؤلفون: | Chen, Hailong, Bisoffi, Andrea, De Persis, Claudio |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science Mathematics |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Systems and Control, Mathematics - Dynamical Systems, Mathematics - Optimization and Control |
| الوصف: | We consider noisy input/state data collected from an experiment on a polynomial input-affine nonlinear system. Motivated by event-triggered control, we provide data-based conditions for input-to-state stability with respect to measurement errors. Such conditions, which take into account all dynamics consistent with data, lead to the design of a feedback controller, an ISS Lyapunov function, and comparison functions ensuring ISS with respect to measurement errors. When solved alternately for two subsets of the decision variables, these conditions become a convex sum-of-squares program. Feasibility of the program is illustrated with a numerical example. Comment: Submitted for peer review on 31 March 2023. To appear in the Proceedings of the 62nd IEEE Conference on Decision and Control, 13-15 December 2023, Singapore |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1109/CDC49753.2023.10383880 |
| URL الوصول: | http://arxiv.org/abs/2309.09050 |
| رقم الانضمام: | edsarx.2309.09050 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1109/CDC49753.2023.10383880 |
|---|