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Recently, the distributed state estimation problem for continuous-time linearsystems over jointly connected switching networks was solved. It was shown thatthe estimation errors will asymptotically converge to the origin by using thegeneralized Barbalat's Lemma. This paper further studies the same problem withtwo new features. First, the asymptotic convergence is strengthened to theexponential convergence. This strengthened result not only offers a guaranteedconvergence rate, but also renders the error system total stability and thus isable to withstand small disturbances. Second, the coupling gains of our localobservers can be distinct and thus offers greater design flexibility, while thecoupling gains in the existing result were required to be identical. These twonew features are achieved by establishing exponential stability for two classesof linear time-varying systems, which may have other applications.

Distributed exponential state estimation of linear systems over jointly connected switching networks