Cyclic Reformulation Based System Identification for Periodically Time-varying Systems

TL;DR

This paper introduces a novel system identification algorithm for linear periodically time-varying plants that achieves high accuracy without requiring specific periodic input signals, using cyclic reformulation and state transformation.

Contribution

The paper presents a new cyclic reformulation-based algorithm for identifying periodically time-varying systems, improving accuracy without specialized input signals.

Findings

High-accuracy models obtained without specific periodic inputs

Algorithm validated through numerical examples

Effective for linear periodically time-varying plants

Abstract

This paper addresses a system identification for linear periodically time-varying plants in the discrete-time setting. A system identification algorithm for linear, periodically time-varying plants is introduced based on a cyclic reformulation and a state coordinate transformation of the cycled system. By using our system identification algorithm, the high-accuracy model of the periodically time-varying plant can be obtained without using specific periodic input signals. The effectiveness of the proposed algorithm is demonstrated with numerical examples.