Sentence examples for matrix inequality conditions from inspiring English sources

Using matrix inequality conditions on the terminal weighting matrix, the closed-loop system stability is guaranteed.

Furthermore, state observers and bilinear matrix inequality conditions are removed in this paper.

The system stability is analyzed by means of linear matrix inequality conditions based on non-quadratic Lyapunov functions.

By defining a parameter-dependent Lyapunov functional, matrix inequality conditions with reduced conservatism are obtained for the design of controllers.

Linear matrix inequality conditions implying interior conic bounds are developed for stable linear time-invariant systems with unknown input delay.

These positive realness conditions are transformed into linear matrix inequality conditions in terms of a state-space realization of the subsystem dynamics, a Lyapunov matrix, and multipliers.

We derive a linear matrix inequality condition which characterizes a relationship between Runge-Kutta coefficients and the corresponding stability region.

Robustness against unstructured model uncertainty is obtained by choosing the cost function parameters so as to satisfy a linear matrix inequality condition.

This "non-square" matrix inequality condition is applied to an anti-windup (AW) problem in which the AW compensator is not activated until the unconstrained control signal reaches a well-defined level beyond that of the physical actuator limits.

It is shown that a more efficient evaluation of robust H2 or H∞ performance can be obtained by a matrix inequality condition which contains additional free parameters as compared to existing characterizations.

When applying this new matrix inequality condition to the robust filter design, these parameters provide extra degrees of freedom in optimizing the guaranteed H2 or H∞ performance and lead to a less-conservative design.