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The feedback is obtained by solving a parameter-dependent linear matrix inequality.
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The filter parameters can be readily designed by solving a set of parameter-dependent linear matrix inequalities (LMIs).
The path between two given targets is obtained by solving a time-dependent optimal control problem.
In addition, the unknown gain matrix is determined by solving a delay-dependent LMI.
The unknown gain matrix is determined by solving a delay-dependent linear matrix inequality.
The observer gain is calculated by solving a delay-dependent matrix differential equation.
The unknown gain matrix is determined by solving a delay-dependent LMI.
Structural shapes are represented by the phase field function defined in the design domain, and this function is optimized by solving a time-dependent reaction diffusion equation.
Stability is proven by a parameter-dependent Lyapunov function.
We further design the scheduler's parameters by solving a dynamic programming (DP) problem.
Optimum values of the independent parameters were determined by solving a multi-objective optimization problem obtained by using the proposed regression models for dependent parameters.
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