This paper studies the synchronization of complex networks with probabilistic interval delay and Markov switching topologies by using a novel dynamic self-triggered control (DSTC) scheme. Employing the probability distribution information of the input time-delay, the control protocol is transformed into a new rule with stochastic parameters. Also, a more general case of switching topologies, Markov switching topologies with partial information on transition rate, is discussed. By introducing a free-connection weighting matrix scheme and using the stability theory, a less conservative synchronization result is derived. It is shown by a numerical example that the DSTC method can reduce the sampling frequency apparently, and the tolerable delay upper bound can also be relaxed. In addition, continuous communication and the Zeno-behavior can be avoided.
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Tan et al. (2019) studied this question.
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