Sentence examples for by introducing slack variables from inspiring English sources

The proposed coupling is eliminated by introducing slack variables.

By introducing slack variables and using parameter dependent Lyapunov functions, the design conservativeness is reduced compared with other existing MPC approaches.

By considering a fuzzy Lyapunov function and by introducing slack variables, we propose the new sufficient stabilization conditions formulated in LMI constraints which can be easily solved using the convex optimization tools.

The problem is first put into canonical form by converting the linear inequalities into equalities by introducing "slack variables" x3 ≥ 0 (so that x1 + x3 = 8), x4 ≥ 0 (so that x2 + x4 = 5), x5 ≥ 0 (so that x1 + x2 + x5 = 10), and the variable x0 for the value of the objective function (so that x1 + 2x2 − x0 = 0).

The problem is first put into canonical form by converting the linear inequalities into equalities by introducing "slack variables" x3 ≥ 0 (so that x1 + x3 = 8), x4 ≥ 0 (so that x2 + x4 = 5), x5 ≥ 0 (so that x1 + x2 + x5 = 10), and the variable x0 for the value of the objective function (so that x1 + 2x2 − x0 = 0).

By introducing slack variables ζ ≥ 0, equation (16) becomes: (19).

By introducing slack variable techniques, sufficient conditions for the design of FD filter are derived in terms of linear matrix inequalities (LMIs).

Moreover, it can eliminate the coupling of Lyapunov matrix variables and system matrices by introducing slack variable that provides additional degree of freedom.

After introducing slack variables and rewriting (40) as in [34], we find the approximate solution of (39) using SeDuMi [37].

Introducing slack variables, the problem described in (5) is equivalent to the following linear program: (6) In our experiments, we implemented and solved this problem using Matlab and the SeDuMi 1.1R3 optimization toolbox (Sturm, 1999).

Without specified structure imposed on introduced slack variables, a flexible filter design method is established in terms of linear matrix inequalities.