4, but in general, the modification may differ largely depending on specific concerned systems.
The concerned systems have certain characteristics, such as unknown nonlinear functions, dynamical uncertainties, unknown control direction and unmeasured state variables.
However, since time delay has not only a fixed value in a practical system [39], the concerned systems with interval time-varying delays were considered in this paper.
By constructing a newly augmented Lyapunov-Krasovskii functional, less conservative sufficient stability conditions of the concerned systems are introduced within the framework of linear matrix inequalities (LMIs).
The sensitivity analysis carried out may be helpful to the decision makers and system engineers for the further improvement of the concerned systems operating under machining environments.
In Theorem 1, the improved robust sufficient stability condition for the concerned systems was proposed by introducing the augmented Lyapunov-Krasovskii functional and using some approaches.
It is assumed that nonlinear functions of the concerned systems are unknown, switching signals are unknown and arbitrary, and the states are unmeasured.
For the real life congestion situations, where the arrival of units depends on the status of the server, our study may be very helpful in the design and development phases of the concerned systems.
These data, which provide information about the location and boundary of the two-phase region of the concerned systems, can be used to examine and develop thermodynamic models like the Predictive Soave Redlich Kwong (PSRK) group contribution equation of state.
Following the idea of single neural network (SNN) approximation, single fuzzy logic system SFLS) approximation is first proposed and synthesized with "minimal learning parameter (MLP)" technique into a novel adaptive fuzzy control design methodology for the concerned systems.
The concerned systems are with a time-varying delay in the state and deficient mode information in the Markov stochastic process, which simultaneously involves the exactly known, partially unknown and uncertain transition rates.
