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Titolo:
ONLINE PROCESS IDENTIFICATION USING THE LAGUERRE SERIES FOR AUTOMATICTUNING OF THE PROPORTIONAL-INTEGRAL-DERIVATIVE CONTROLLER
Autore:
PARK HI; SUNG SW; LEE IB; LEE J;
Indirizzi:
POHANG UNIV SCI & TECHNOL,SCH ENVIRONM ENGN,DEPT CHEM ENGN,SAN 31 HYOJA DONG POHANG 790784 SOUTH KOREA POHANG UNIV SCI & TECHNOL,SCH ENVIRONM ENGN,DEPT CHEM ENGN POHANG 790784 SOUTH KOREA KYUNGPOOK NATL UNIV,DEPT CHEM ENGN TAEGU 702701 SOUTH KOREA
Titolo Testata:
Industrial & engineering chemistry research
fascicolo: 1, volume: 36, anno: 1997,
pagine: 101 - 111
SICI:
0888-5885(1997)36:1<101:OPIUTL>2.0.ZU;2-Q
Fonte:
ISI
Lingua:
ENG
Soggetto:
2ND-ORDER PARAMETERS; DELAY SYSTEMS; APPROXIMATION; TRANSIENT; SINGLE; MODELS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
27
Recensione:
Indirizzi per estratti:
Citazione:
H.I. Park et al., "ONLINE PROCESS IDENTIFICATION USING THE LAGUERRE SERIES FOR AUTOMATICTUNING OF THE PROPORTIONAL-INTEGRAL-DERIVATIVE CONTROLLER", Industrial & engineering chemistry research, 36(1), 1997, pp. 101-111

Abstract

A new on-line identification method based on the approximation of closed-loop response is proposed to tackle the shortcomings of previous autotuning methods using a proportional controller as a test signal generator. That is, for both the overdamped and the underdamped closed-loop response in the identification step, the proposed method can easilyestimate the second-order plus time delay model only with the measurements of the transient. From the orthonormal property of the Laguerre series, the closed-loop response in the identification step is approximated by a simple least-squares technique effectively, and then a high-order process transfer function is estimated from it. Finally, a simple model reduction method is used to reduce the high-order process transfer function to a second-order plus time delay model via the least-squares technique in the frequency domain. The proposed method does notneed any numerical technique such as root-finding or iterative optimization Since it uses all the measurements of transient response instead of several dominant data points such as peak or valley values, the robustness to the measurement noise is greatly enhanced. From simulation results and comparisons with previous works, we can recognize that it provides more accurate models and better control performances for various process dynamics. In experimental study, it can be noted that itis also very effective in identification and control of real processes.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 14/07/20 alle ore 09:48:11