The original model has 332 degrees of freedom, and, therefore, the system was underdetermined and appropriate for the utilization of optimization-based methods, such as the ones based on linear programming approaches.
The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices.
In general, fuzzy regression methods are divided into two categories: the first one is based on linear programming (LP) approach and the second one is based on the fuzzy least squares (FLS) approach.
Because the reduced feasible set is defined in (3) by linear constraints, we propose an alternative algorithm to the EM-based approach based on linear programming (LP) to compute the FBID of a perturbation.
The predicted fatigue lives based on linear fracture mechanics approach were in agreement with the experimental results below the critical nominal stress amplitude.
By using a stochastic Lyapunov function which is dependent on the jump mode, design procedures for a mode-dependent state feedback controller are developed based on linear matrix inequality approach.
Based on linear matrix inequality (LMI) approach, a delay-dependent stability criteria has been developed.
Based on linear matrix inequality (LMI) approach, a method for designing a reliable fuzzy controller is presented.
Based on linear matrix inequality (LMI) approach, we design a state feedback controller, which guarantees that, for all admissible uncertainties, the resultant closed-loop system is regular, impulse free, and stable with an H∞ norm bound constraint.
Based on Linear Matrix Inequalities, two different approaches are proposed.
