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Combining with capturing the characteristic of sampled-data systems with a novel piecewise Lyapunov Krasovskii functional (LKF), a less complex and less conservative H∞ stabilization criterion is formulated as linear matrix inequalities (LMIs), which can be easily checked by using standard numerical software.
Due to its features, the final resolving system can be solved with the classical approaches by using standard numerical procedures.
The corresponding full-order filter design is cast into a convex optimization problem, which can be efficiently handled by using standard numerical algorithms.
Since these conditions involve matrix equalities, the cone complementarity linearization procedure is employed to cast the nonconvex feasibility problem into a sequential minimization problem subject to linear matrix inequalities, which can be readily solved by using standard numerical software.
Sufficient conditions are formulated in terms of linear matrix inequalities (LMIs), and the corresponding filter design is cast into a convex optimization problem which can be efficiently handled by using standard numerical algorithms.
Different from the traditional quadratic framework, the synthesis problem is solved by exploiting the cone complementarity linearization (CCL) method, together with a sequential minimization problem subject to LMI constraints obtained for the existence of admissible controllers, which can be readily solved by using standard numerical software.
Similar(52)
As in the undirected case, we compute the probability that one instance of XY transitions to another along a branch of length t by determining P = exp[Qt], using standard numerical Eigen-decomposition techniques [36].
The proposed filter can be obtained by solving the LMI, which can be easily facilitated using standard numerical packages.
The numerical solution of these equations is straight-forward using standard numerical techniques.
Patchy patterns were computed using standard numerical methods on a regular grid.
By employing the Wirtinger inequality and extended Jensen inequality, some sufficient conditions of the sampled-data control for T-S fuzzy systems are established, which are efficiently solved by using standard available numerical packages.
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