Reconstructing Indistinguishable Solutions Via Set-Valued KKL Observer

TL;DR

This paper extends the KKL observer framework to cases where solutions are indistinguishable based on output, introducing a set-valued observer that converges to backward-indistinguishable sets and can reconstruct multiple solutions.

Contribution

It develops a set-valued KKL observer for indistinguishable solutions, proving convergence and solution reconstruction under new assumptions.

Findings

Set-valued KKL observer converges in Hausdorff sense.

Observer can asymptotically reconstruct multiple solutions.

Conditions for existence of Lipschitz set-valued inverse are established.

Abstract

KKL observer design consists in finding a smooth change of coordinates transforming the system dynamics into a linear filter of the output. The state of the original system is then reconstructed by implementing this filter from any initial condition and left-inverting the transformation, under a \textit{backward-distinguishability} property. In this paper, we consider the case where the latter assumption does not hold, namely when distinct solutions may generate the same output, and thus be indistinguishable. The KKL transformation is no longer injective and its ``left-inverse'' is thus allowed to be set-valued, yielding a set-valued KKL observer. Assuming the transformation is full-rank and its preimage has constant cardinality, we show the existence of a globally defined set-valued left-inverse that is Lipschitz in the Hausdorff sense. Leveraging on recent results linking this left-inverse with the \textit{backward-indistinguishable sets}, we show that the set-valued KKL observer converges in the Hausdorff sense to the backward-indistinguishable set of the system solution. When, additionally, a given output is generated by a specific number of solutions not converging to each other, we show that the designed observer asymptotically reconstructs each of those solutions. Finally, the different assumptions are discussed and illustrated via examples.