Data Driven Control Eigensystem Realization

In this lecture, we describe the

In this lecture, we introduce the

In this lecture, we explore the observer Kalman filter identification (OKID) and

Overview lecture on linear system identification and model reduction. This lecture discusses how we obtain reduced-order models ...

Overview lecture for series on

This lecture discusses the eigenvalue

In this lecture, we describe how the discrete-time impulse response is used in the

In this lecture, we introduce the observer Kalman filter identification (OKID) algorithm. OKID takes natural input--output

In this lecture, we discuss the overarching goal of balanced model reduction: Identifying key states that are most jointly ...

In this lecture, we connect the

In this lecture, we introduce the balancing proper orthogonal decomposition (BPOD) to approximate balanced truncation for ...

The slides may be obtained at: http://

In this lecture, we explore balanced truncation and BPOD on a numerical example in Matlab.