0000000000020913
AUTHOR
Changhong Wang
New delay-dependent stability of Markovian jump neutral stochastic systems with general unknown transition rates
This paper investigates the delay-dependent stability problem for neutral Markovian jump systems with generally unknown transition rates GUTRs. In this neutral GUTR model, each transition rate is completely unknown or only its estimate value is known. Based on the study of expectations of the stochastic cross-terms containing the integral, a new stability criterion is derived in terms of linear matrix inequalities. In the mathematical derivation process, bounding stochastic cross-terms, model transformation and free-weighting matrix are not employed for less conservatism. Finally, an example is provided to demonstrate the effectiveness of the proposed results.
A sliding mode approach to H∞ non-fragile observer-based control design for uncertain Markovian neutral-type stochastic systems
This paper is focused on designing an H ∞ sliding-mode control for a class of neutral-type stochastic systems with Markovian switching parameters and nonlinear uncertainties. An H ∞ non-fragile observer subjected to the transition rates of the switching mode is firstly constructed. By some specified matrices, the connections among the designed sliding surfaces corresponding to every mode are established. Then, the state-estimation-based sliding mode control law is designed to guarantee the reachability of the sliding surface in finite time interval. Furthermore, a stochastic stability criterion is established for all admissible uncertainties, which can guarantee the error system and sliding…
Global stability of coupled Markovian switching reaction–diffusion systems on networks
Abstract In this paper, we investigate the stability problem for some Markovian switching reaction–diffusion coupled systems on networks (MSRDCSNs). By using the Lyapunov function, we establish some novel stability principles for stochastic stability, asymptotically stochastic stability, globally asymptotically stochastic stability and almost surely exponential stability of the MSRDCSNs. These stability principles have a close relation to the topology property of the network. We also provide a systematic method for constructing global Lyapunov function for these MSRDCSNs by using graph theory. The new method can help analyze the dynamics of complex networks.