Protocol-based H∞ estimation for Markovian jumping delayed systems with partially unknown transition probability

This article pays attention to estimation issue for the state of a particular kind of Markovian jumping delayed systems (MJDSs) with exogenous disturbances. The transition probability of Markovian process is assumed to be partially unknown for accurately reflecting the real complexity of mode switching. To avoid data collision while retaining the necessary requirement of information updating, a scheduling named MEF-TOD protocol is adopted to dynamically allocate access authorization of sensor nodes to estimator. By virtue of binary delta operator, a mode-dependent estimator is built to asymptotically approximate the real state of original system. Through taking a suitable energy functional and exploiting stochastic analysis method, several novel approaches are given to sufficiently make the error asymptotically stable under constraint of $H_{\infty }$ performance. The gain matrices for estimator are ultimately formed through settling a series of inequalities of matrix. At last, a numerical instance exhibits the validity of proposed results.