Sentence examples for observer matrix from inspiring English sources

The design of the observer matrix gain is achieved by solving a Linear Matrix Inequality (LMI) feasibility problem, where constraints on the position in the complex plane of the poles of the estimation error dynamics are taken into account.

Further, we present one assertion related to one spectral inequality arisen in the process of assigning stable spectrum to the observer matrix and show its use in the observer design.

Specifically, is it that the Kalman gain in Eq. (10) has been replaced by a tuned asymptotic observer matrix that is now merely tuned for algorithm convergence kinetics and thus independent of the model?

The control and observer matrices can be solved directly by using the existing LMI optimization techniques.

The complete and parametric solutions for the observer matrices and for the generalized eigenvectors are obtained.

Using this approach, linear matrix inequality (LMI) conditions are derived to guarantee stability of the estimation error dynamics and to compute the observer matrices.

For some special cases, it is shown that the sufficient condition can be formulated in terms of linear matrix inequalities (LMIs), and the observer matrices can be attained by solving a set of LMIs.

The observer gain matrix, the controller gain matrix and the event-driven parameters are co-designed and co-obtained in terms of solution to a set of linear matrix inequalities (LMIs).

A sufficient solvable condition of the FDF problem is derived and a solution of observer gain matrix is obtained in terms of linear matrix inequality.

The observer gain matrix is determined by solving an algebraic Riccati equation.

The case of immeasurable state is considered where the observer gain matrix is solved by Sylvester equation.