On Topological Properties of the Set of Stabilizing Feedback Gains
Not on the map. Why?
Abstract (arXiv)
This work presents a fairly complete account on various topological and metrical aspects of feedback stabilization for single-input-single-output (SISO) continuous and discrete time linear-time-invariant (LTI) systems. In particular, we prove that the set of stabilizing output feedback gains for a SISO system with n states has at most lceilfracn2rceil connected components. Furthermore, our analysis yields an algorithm for determining intervals of stabilizing gains for general continuous and discrete LIT systems; the proposed algorithm also computes the number of unstable roots in each unstable interval. Along the way, we also make a number of observations on the set of stabilizing state feedback gains for MIMO systems.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Apr 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 2; 2025: 1; 2026: 2.
5 papers.
- 2024Model-Free Learning for the Linear Quadratic Regulator over Rate-Limited Channelscited by 2
- 2024Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradientcited by 1
- 2025Policy Gradient Method for LQG Control via Input-Output-History Representation: Convergence to O(ε)-Stationary Pointscited by 1
- 2026Model-Free Output Feedback Stabilization via Policy Gradient Methodscited by 1
- 2026On the Optimization Landscape of Observer-based Dynamic Linear Quadratic Controlcited by 0
- 2026On the Optimization Landscape of Observer-based Dynamic Linear Quadratic Control12 Apr 2026
- 2026Model-Free Output Feedback Stabilization via Policy Gradient Methods27 Jan 2026
- 2025Policy Gradient Method for LQG Control via Input-Output-History Representation: Convergence to O(ε)-Stationary Points22 Oct 2025
- 2024Stability-Certified On-Policy Data-Driven LQR via Recursive Learning and Policy Gradient8 Mar 2024
- 2024Model-Free Learning for the Linear Quadratic Regulator over Rate-Limited Channels2 Jan 2024