Stability and Stabilization of Switched Linear Systems With Mode-Dependent Average Dwell TimeXudong Zhao, Lixian Zhang, Peng Shi et al.|IEEE Transactions on Automatic Control|2011 In this paper, the stability and stabilization problems for a class of switched linear systems with mode-dependent average dwell time (MDADT) are investigated in both continuous-time and discrete-time contexts. The proposed switching law is more applicable in practice than the average dwell time (ADT) switching in which each mode in the underlying system has its own ADT. The stability criteria for switched systems with MDADT in nonlinear setting are firstly derived, by which the conditions for stability and stabilization for linear systems are also presented. A numerical example is given to show the validity and potential of the developed techniques.
Stochastic Synchronization of Markovian Jump Neural Networks With Time-Varying Delay Using Sampled DataZheng‐Guang Wu, Peng Shi, Hongye Su et al.|IEEE Transactions on Cybernetics|2013 In this paper, the problem of sampled-data synchronization for Markovian jump neural networks with time-varying delay and variable samplings is considered. In the framework of the input delay approach and the linear matrix inequality technique, two delay-dependent criteria are derived to ensure the stochastic stability of the error systems, and thus, the master systems stochastically synchronize with the slave systems. The desired mode-independent controller is designed, which depends upon the maximum sampling interval. The effectiveness and potential of the obtained results is verified by two simulation examples.