Subspace Identification for Linear Periodically Time-varying Systems*

Identification of Linear Periodically Time-Varying (LPTV) Systems

A linear periodically time-varying (LPTV) system is a linear time-varying system with the coefficients changing periodically, which is widely used in control, communications, signal processing, and even circuit modeling. This thesis concentrates on identification of LPTV systems. To this end, the representations of LPTV systems are thoroughly reviewed. Identification methods are developed accor...

Realization and identification of autonomous linear periodically time-varying systems

Subsampling of a linear periodically time-varying system results in a collection of linear time-invariant systems with common poles. This key fact, known as “lifting”, is used in a two step realization method. The first step is the realization of the time-invariant dynamics (the lifted system). Computationally, this step is a rank-revealing factorization of a block-Hankel matrix. The second ste...

Noncausal linear periodically time-varying scaling for discrete-time systems

A novel technique called noncausal linear periodically time-varying (LPTV) scaling was introduced recently, and it was shown that even static noncausal LPTV scaling has an ability of inducing frequency-dependent scaling if it is interpreted in the context of the conventional scaling approach. Motivated by this preceding study of ours, this paper studies to exploit this attractive property and d...

Subspace Identification for Linear Systems

Recursive Subspace Prediction of Linear Time - Varying Stochastic Systems

In this paper, a new subspace method for predicting time-invariant/varying stochastic systems is investigated in the 4SID framework. Using the concept of angle between past and current subspaces spanned by the extended observability matrices, the future subspace is predicted by rotating current subspace in the geometrical sense. In order to treat even time-varying system, a recursive algorithm ...