Extended dissipative filtering for singularly perturbed systems with random uncertain measurement: A double-layer switching mechanism

Abstract

This article concentrates on the extended dissipative filtering for slow sampling singularly perturbed systems based on the double-layer switching mechanism containing the Markov jump signal and the persistent dwell-time switching signal simultaneously. The Markov jumping signal, as the upper layer switching signal, is utilized to describe the jumping of system modes. Then, the persistent dwell-time switching signal is introduced as a lower layer switching signal to characterize the variation for transition probabilities of the Markov chain. Besides, the uncertainties of actual measurement output are assumed to randomly occur, which are described by a set of Bernoulli distributed white sequences. Furthermore, some sufficient conditions ensuring the filtering error system being mean-square exponentially stable with an extended dissipative performance are obtained through the Lyapunov stability theory and some advanced linear matrix transformation techniques. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed method.