pith. sign in

arxiv: 1809.05289 · v1 · pith:4VNKH5B5new · submitted 2018-09-14 · 🧮 math.OC

Lyapunov Theory for Discrete Time Systems

classification 🧮 math.OC
keywords timetheorysystemsaveragingconditionscontinuousexponentialfunction
0
0 comments X
read the original abstract

In this work, we present the equivalent of many theorems available for continuous time systems. In particular, the theory is applied to Averaging Theory and Separation of time scales. In particular the proofs developed for Averaging Theory and Separation of time scales departs from those typically used in continuous time systems that are based on twice differentiable change of variables and the multiple use of the Implicit Function Theorem and Mean Value Theorem. More specifically, by constructing a suitable Lyapunov function only Lipschitz conditions are necessary. Finally, it is shown that under mild condition on the so-called "interconnection conditions" the proposed tools can guarantee semi-global exponential stability rather than the more stringent local exponential stability typically found in the literature

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Implicit score-driven filters for time-varying parameter models

    stat.ME 2025-12 unverdicted novelty 6.0

    Implicit score-driven updates preserve the full observation density to deliver global stability and mean-squared-error contraction toward the pseudo-true parameter for log-concave densities in time-varying parameter models.

  2. Finite-Step Invariant Sets for Hybrid Systems with Probabilistic Guarantees

    eess.SY 2026-04 unverdicted novelty 5.0

    A sampling-based optimization framework computes finite-step invariant ellipsoids for hybrid system return maps with user-specified probabilistic guarantees on invariance.