arXiv Open Access 2023

Stability Bounds for Learning-Based Adaptive Control of Discrete-Time Multi-Dimensional Stochastic Linear Systems with Input Constraints

Seth Siriya Jingge Zhu Dragan Nešić Ye Pu

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Abstrak

We consider the problem of adaptive stabilization for discrete-time, multi-dimensional linear systems with bounded control input constraints and unbounded stochastic disturbances, where the parameters of the true system are unknown. To address this challenge, we propose a certainty-equivalent control scheme which combines online parameter estimation with saturated linear control. We establish the existence of a high probability stability bound on the closed-loop system, under additional assumptions on the system and noise processes. Finally, numerical examples are presented to illustrate our results.

Topik & Kata Kunci

eess.SY cs.LG math.OC

Penulis (4)

Seth Siriya

Jingge Zhu

Dragan Nešić

Ye Pu

Format Sitasi

APA MLA BibTeX

Siriya, S., Zhu, J., Nešić, D., Pu, Y. (2023). Stability Bounds for Learning-Based Adaptive Control of Discrete-Time Multi-Dimensional Stochastic Linear Systems with Input Constraints. https://arxiv.org/abs/2304.00569

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Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓