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Meanwhile, the gains of the finite-time controller could be designed by solving some linear matrix inequalities.
Specifically, a switching static output-feedback fuzzy-model-based controller is designed by solving some linear matrix inequalities (LMI), which are derived from the developed local representations.
Based on the optimal robust H∞ performance analysis of the SNNM, the parameters of output feedback controllers can be obtained by solving some linear matrix inequalities (LMIs).
It is shown that the two parameters of a FDFC, i.e., the controller gain and the upper bound of controller time delay, can be simultaneously obtained by solving some linear matrix inequalities.
The feedback gain and the quantizer parameters that guarantee the internal stability and the disturbance rejection performance of the closed-loop system are obtained by solving some linear matrix inequalities.
First a scaled state vector is defined such that the objective function contours in the defined optimization problem become vertical or horizontal ellipses or circles, and then the control input is determined at each sampling time as a state feedback that minimizes the infinite horizon objective function by solving some linear matrix inequalities.
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Based on this condition, the filter design method is proposed, and by solving some convex linear matrix inequalities, the explicit of the desired filer gain matrices is also given.
In order to ensure the strict feasibility of the optimal solution, in the lower-level of program, the constraints are imposed on the confidence upper bounds of the structural responses, which can be obtained efficiently by solving some convex linear semi-definite programs (LSDPs).
Individual rate constants are then calculated by solving linear or non-linear algebraic equations.
Specifically, iterative methods compute reconstructions by solving the linear system iteratively, reducing the projection error in some vector norm in each iteration.
A cost criterion is established to determine cost-factor ranges for optimality of the primary cases, and results validated by solving linear programming (LP) and mixed integer linear programming (MILP) formulations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com