Asynchronous State Estimator Design for Markov Switched Systems with Incomplete Probabilities and Redundant Channels

This paper is concerned about the
$H_{\infty}$
asynchronous state estimator design for Markov switched systems (MSSs) with incomplete transition probabilities and redundant channels. A hidden Markov chain (HMC) is introduced to characterize the asynchronous degree between the state estimator mode and the system mode. Firstly an asynchronous full-order state estimator is devised for the MSSs. Then, by Lyapunov functional and stochastic analysis, new criteria are derived such that the augmented system consisting of the target system and state estimator is
$H_{\infty}$
stochastically finite-time boundedness. After that, with matrix decoupling technique, a design algorithm is obtained in form of linear matrix inequalities (LMIs). Finally, the practical one-link robotic manipulator is utilized to validate the developed results.