arXiv Open Access 2022

Learning-Based Adaptive Control for Stochastic Linear Systems with Input Constraints

Seth Siriya Jingge Zhu Dragan Nešić Ye Pu

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Abstrak

We propose a certainty-equivalence scheme for adaptive control of scalar linear systems subject to additive, i.i.d. Gaussian disturbances and bounded control input constraints, without requiring prior knowledge of the bounds of the system parameters, nor the control direction. Assuming that the system is at-worst marginally stable, mean square boundedness of the closed-loop system states is proven. Lastly, 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. (2022). Learning-Based Adaptive Control for Stochastic Linear Systems with Input Constraints. https://arxiv.org/abs/2209.07040

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓