Data-driven design of structured sparse feedback controllers
Abstrak
This article proposes a data-driven design method of structured sparse feedback controllers. In situations where the system model is unavailable but the measurement data are available, we address the problem of finding a feedback controller which minimizes the number of nonzero rows in the feedback gain such that the closed-loop system has stability with the guaranteed rate of convergence. It is shown that this problem can be reduced to a nonconvex optimization problem with a constraint described by a linear matrix inequality. Moreover, its convex relaxation problem is also considered. To demonstrate the effectiveness of our approach, a numerical example is provided. Furthermore, as an application of the above results, we develop a data-driven design method of block-structured sparse feedback controllers.
Topik & Kata Kunci
Penulis (3)
Takumi Iwata
Shun-ichi Azuma
Masaaki Nagahara
Akses Cepat
- Tahun Terbit
- 2025
- Sumber Database
- DOAJ
- DOI
- 10.1080/18824889.2025.2550853
- Akses
- Open Access ✓