Identifiability of Linear Time Invariant System

Kernels for linear time invariant system identification

In this paper, we study the problem of identifying the impulse response of a linear time invariant (LTI) dynamical system from the knowledge of the input signal and a finite set of noisy output observations. We adopt an approach based on regularization in a Reproducing Kernel Hilbert Space (RKHS) that takes into account both continuous and discrete time systems. The focus of the paper is on des...

Linear Time-invariant Systems

control scheme, in which different time scales for the rigid body subsystem dynamics and for the flexible dynamics are used (Canudas de Wit et al., 1996). An application of the two-time scale method is shown, for example, in Kang, Yeung, and Mills (2002). In summary, the aim of the authors to provide an upperlevel undergraduate and graduate textbook and a reference for experienced professionals...

AN ALGORITHM FOR FINDING THE STABILITY OF LINEAR TIME-INVARIANT SYSTEMS

The purpose of this paper is to show that the ideas and techniques of the classical methods of finding stability, such as the criteria of Leonhard and Nyquist, can be used to derive simple algorithm to verify stability. This is enhanced by evaluating the argument of the characteristic equation of a linear system in the neighbourhood of the origin of the complex plane along the imaginary axis

System identifiability from finite time series

The possibility to identify linear systems from finite data, e.g. a partial impulse response, is determined by the degree of corroboration of system restrictions by the observed data. Ala~'Kt-In this paper we investigate the identification of systems from time series observed over a finite time interval. The data generating system is supposed to be finite dimensional, linear and time invariant,...

Linear Time-Invariant Systems with Discrete Time