Integrated system identification and PID controller tuning by frequency loop-shaping

Elena Grassi; Konstantinos Tsakalis; Sachi Dash; Sujit V. Gaikwad; Ward MacArthur; Gunter Stein

Integrated system identification and PID controller tuning by frequency loop-shaping

Elena Grassi, Konstantinos Tsakalis, Sachi Dash, Sujit V. Gaikwad, Ward MacArthur, Gunter Stein

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

A systematic design methodology for Proportional-Integral-Derivative controllers is presented. Starting from data sets, a model of the system and its uncertainty bounds are obtained. The parameters of the controller are tuned by a convex optimization algorithm, minimizing a weighted difference between the actual loop transfer function and a target in an L ₂/L _∞ sense. The target selection is guided by the identified model and its uncertainty. The problem of disjoint data sets and/or different models for the same system is also addressed. The method has proved successful in numerous practical cases showing both expediency in controller design and implementation and improved performance over existing controllers.

Original language	English (US)
Title of host publication	Proceedings of the IEEE Conference on Decision and Control
Publisher	IEEE
Pages	1517-1522
Number of pages	6
Volume	2
State	Published - 1999
Event	The 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA Duration: Dec 7 1999 → Dec 10 1999

Other

Other	The 38th IEEE Conference on Decision and Control (CDC)
City	Phoenix, AZ, USA
Period	12/7/99 → 12/10/99

ASJC Scopus subject areas

Chemical Health and Safety
Control and Systems Engineering
Safety, Risk, Reliability and Quality

Cite this

@inproceedings{227a5ac208cf409faef4137ca5d64c25,

title = "Integrated system identification and PID controller tuning by frequency loop-shaping",

abstract = "A systematic design methodology for Proportional-Integral-Derivative controllers is presented. Starting from data sets, a model of the system and its uncertainty bounds are obtained. The parameters of the controller are tuned by a convex optimization algorithm, minimizing a weighted difference between the actual loop transfer function and a target in an L 2/L ∞ sense. The target selection is guided by the identified model and its uncertainty. The problem of disjoint data sets and/or different models for the same system is also addressed. The method has proved successful in numerous practical cases showing both expediency in controller design and implementation and improved performance over existing controllers. ",

author = "Elena Grassi and Konstantinos Tsakalis and Sachi Dash and Gaikwad, {Sujit V.} and Ward MacArthur and Gunter Stein",

year = "1999",

language = "English (US)",

volume = "2",

pages = "1517--1522",

booktitle = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "IEEE",

note = "The 38th IEEE Conference on Decision and Control (CDC) ; Conference date: 07-12-1999 Through 10-12-1999",

}

TY - GEN

T1 - Integrated system identification and PID controller tuning by frequency loop-shaping

AU - Grassi, Elena

AU - Tsakalis, Konstantinos

AU - Dash, Sachi

AU - Gaikwad, Sujit V.

AU - MacArthur, Ward

AU - Stein, Gunter

PY - 1999

Y1 - 1999

N2 - A systematic design methodology for Proportional-Integral-Derivative controllers is presented. Starting from data sets, a model of the system and its uncertainty bounds are obtained. The parameters of the controller are tuned by a convex optimization algorithm, minimizing a weighted difference between the actual loop transfer function and a target in an L 2/L ∞ sense. The target selection is guided by the identified model and its uncertainty. The problem of disjoint data sets and/or different models for the same system is also addressed. The method has proved successful in numerous practical cases showing both expediency in controller design and implementation and improved performance over existing controllers.

AB - A systematic design methodology for Proportional-Integral-Derivative controllers is presented. Starting from data sets, a model of the system and its uncertainty bounds are obtained. The parameters of the controller are tuned by a convex optimization algorithm, minimizing a weighted difference between the actual loop transfer function and a target in an L 2/L ∞ sense. The target selection is guided by the identified model and its uncertainty. The problem of disjoint data sets and/or different models for the same system is also addressed. The method has proved successful in numerous practical cases showing both expediency in controller design and implementation and improved performance over existing controllers.

UR - http://www.scopus.com/inward/record.url?scp=0033332966&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033332966&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0033332966

VL - 2

SP - 1517

EP - 1522

BT - Proceedings of the IEEE Conference on Decision and Control

PB - IEEE

T2 - The 38th IEEE Conference on Decision and Control (CDC)

Y2 - 7 December 1999 through 10 December 1999

ER -

Integrated system identification and PID controller tuning by frequency loop-shaping

Abstract

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this