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A. Pogromsky

Publications and source records attributed to A. Pogromsky.

2 recordsLinked to original sources

Contraction theory: Hausdorff--Riemann Measures as Set-Based Lyapunov Functions

We offer a measure-theoretic extension of the concept and theory of $k$-contraction, including their generalization on fractional dimensions $d$. The respective contraction property is defined through the exponential decay of the $d$-dimensional volume of compact sets transported by a nonlinear flow. For autonomous systems on positively invariant compact sets, we derive comprehensive, i.e., necessary and sufficient, conditions for $d$-contractivity in two complementary forms. The first is expressed in terms of the finite-time Lyapunov characteristic exponents and is akin in spirit to the first Lyapunov method. The second one is consonant with the second Lyapunov method and relies on existence of a Riemannian metric ensuring exponential decay of the metric-induced $d$-dimensional Hausdorff measure. To acquire monotone measure-theoretic-based Lyapunov functions, we introduce a family of \emph{Hausdorff-Riemann measures}, which are elliptic, metric-dependent $d$-measures that strictly decrease along the trajectories and thus may serve as Lyapunov functions. These measures enable an anytime characterization of the rate of contraction and provide constructive tools for stability analysis and feedback design. To illustrate the applicability of the approach, we derive tractable criteria for orbital stability of periodic solutions of autonomous ODE's and employ several prototypical particular examples, including a rigid body with dissipation and constant torque, the R\"ossler system, and the Langford system.

math.DS

Remote state estimation problem: towards the data-rate limit along the avenue of the second Lyapunov method

In the context of control and estimation under information constraints, restoration entropy measures the minimal required data rate above which the state of a system can be estimated so that the estimation quality does not degrade over time and, conversely, can be improved. The remote observer here is assumed to receive its data through a communication channel of finite bit-rate capacity. In this paper, we provide a new characterization of the restoration entropy which does not require to compute any temporal limit, i.e., an asymptotic quantity. Our new formula is based on the idea of finding a specific Riemannian metric on the state space which makes the metric-dependent upper estimate of the restoration entropy as tight as one wishes.

math.OC