.png){kind=icon}
.png){kind=icon}
Return
Polyhedral control design: Theory and methods
.png){kind=icon}
OA
AI
DOI：10.1016/j.arcontrol.2025.100992.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this article, we survey the primary research on polyhedral computing methods for constrained linear control systems. Our focus is on the modeling power of convex optimization, featured in the design of set-based robust and optimal controllers. In detail, we review the state-of-the-art techniques for computing geometric structures such as robust control invariant polytopes. Moreover, we survey recent methods for constructing control Lyapunov functions with polyhedral epigraphs as well as the extensive literature on robust model predictive control. The article concludes with a discussion of both the complexity and potential of polyhedral computing methods that rely on large-scale convex optimization.
Keywords:
Polyhedral computing
Convex optimization
Linear systems
Optimal control
Robust control
Model predictive control
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
10.7
Papers:
828
Citations:
5.9K
Organization
View more organizations