Open AccessFractional‐order repetitive control of programmable AC power sources
Author(s) -
Zou Zixiang,
Zhou Keliang,
Wang Zheng,
Cheng Ming
Publication year - 2014
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2013.0429
Subject(s) - control theory (sociology) , waveform , repetitive control , harmonic , variable (mathematics) , computer science , power (physics) , filter (signal processing) , automatic frequency control , mathematics , control system , telecommunications , engineering , acoustics , electrical engineering , physics , control (management) , quantum mechanics , artificial intelligence , mathematical analysis , radar , computer vision
Programmable AC power sources that provide variable‐frequency and variable‐amplitude output voltages are widely used in automatic testing equipment and bench top applications. Under various load conditions, a high‐performance programmable AC power source not only can generate very clean sinusoidal output voltages, but also to accurately synthesise specified harmonic distorted wave‐shapes. Digital repetitive control (RC) can achieve zero steady‐state error tracking of any periodic signal with known integer period, but usually fails to provide precise tracking of variable‐frequency periodical waveform with fractional period. In this study, a frequency adaptive fractional‐order RC (FORC) strategy at fixed sampling rate is proposed to track or eliminate any periodic signals with variable frequency, where a Lagrange interpolation‐based fractional delay filter is used to approximate the factional delay items in RC. The proposed FORC that offers fast on‐line tuning of the fractional delay and the fast update of the coefficients, provide a simple but high‐performance real‐time control approach to dealing with variable‐frequency variable‐magnitude periodic signals. A case study of FORC‐based programmable AC power source is conducted. Experimental results are provided to show the effectiveness of the proposed FORC strategy. It can be widely used in extensive applications.