mlsanityData to 7 Oct 2026

Stable Online Control of Linear Time-Varying Systems

arXiv 2104.14134 ↗First posted 29 Apr 2021math.OC cs.LG cs.SYcited by 3

Not on the map. Why?

Abstract (arXiv)

Linear time-varying (LTV) systems are widely used for modeling real-world dynamical systems due to their generality and simplicity. Providing stability guarantees for LTV systems is one of the central problems in control theory. However, existing approaches that guarantee stability typically lead to significantly sub-optimal cumulative control cost in online settings where only current or short-term system information is available. In this work, we propose an efficient online control algorithm, COvariance Constrained Online Linear Quadratic (COCO-LQ) control, that guarantees input-to-state stability for a large class of LTV systems while also minimizing the control cost. The proposed method incorporates a state covariance constraint into the semi-definite programming (SDP) formulation of the LQ optimal controller. We empirically demonstrate the performance of COCO-LQ in both synthetic experiments and a power system frequency control example.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 6 of its 29 references that are in the map. First posted on arXiv 29 Apr 2021.

Builds on

6 of 29 references.

References · 6

  1. 2018Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulatorcited by 86
  2. 2018Online Linear Quadratic Controlcited by 55
  3. 2020Adaptive Regret for Control of Time-Varying Dynamicscited by 38
  4. 2017Learning-based Control of Unknown Linear Systems with Thompson Samplingcited by 10
  5. 2020Regret-optimal control in dynamic environmentscited by 5
  6. 2013Impact of Low Rotational Inertia on Power System Stability and Operationcited by 4

Built on by

Cited by year

Citing papers per year: 2022: 3.

3 papers.