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In stability analysis, the upper bounds of time delays and packet dropouts are both given in terms of the Lyapunov theorem.
And some numerical examples are presented to illustrate the effectiveness of the proposed method due to the significant improvement in the allowable upper bounds of time delays.
Table 1 shows that the upper bounds of time delay decrease when there exist unknown elements of a transition rates matrix.
Table 1 also illustrates the effectiveness and less conservatism of Theorems 3.1-3.2 3.1-3.2the significant improvement in the allowable upper boundueof tome delays.
Moreover, numerical example illustrates the effectiveness and less conservatism of all the proposed methods via the significant improvement in the allowable upper bounds of time delays.
By Theorem 3.1, the null solution of impulsive Markovian jumping stochastic fuzzy system (1.1) is globally stochastically exponentially stable in the mean square with the convergence rate 0.00185 and the allowable upper bounds of time delays τ = 14.
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These circumstances are reliant on both the lower and upper bounds of time-varying delays.
where μ 1 = min { μ 1 i, i ∈ N } and μ 2 = max { μ 2 i, i ∈ N } are prescribed integers representing the lower and upper bounds of time-varying delay τ i ( t ).
Similarly, h 1 = min { h 1 i, i ∈ N } and h 2 = max { h 2 i, i ∈ N } are prescribed integers representing the lower and upper bounds of time-varying delay τ ˙ i ( t ).
This upper bound of time is called the PQT constraint.
In this case, the infimum of the control time span should be larger than the upper bound of time delay.
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