Adaptive robust control (convergence, stability and performance)

Graham C. Goodwin; David J. Hill; David Q. Mayne; Richard H. Middleton

doi:10.1109/cdc.1986.267301

Adaptive robust control (convergence, stability and performance)

Graham C. Goodwin, David J. Hill, David Q. Mayne, Richard H. Middleton

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

13 Citations (Scopus)

Abstract

The authors show that a robust adaptive controller can be developed which stabilizes all members of a wide class of systems. The class of systems includes those having significant unmodeled dynamics and nonminimum phase characteristics. The theoretical results are supported by experimental evidence of the claimed robustness properties. The success of the algorithm is a result of the amalgamation of various techniques including regression vector filtering, pole assignment, estimator deadzone, least squares and internal model principle.

Original language	English
Title of host publication	1986 25th IEEE Conference on Decision and Control
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	468-473
Number of pages	6
DOIs	https://doi.org/10.1109/cdc.1986.267301
Publication status	Published - 1986
Externally published	Yes
Event	IEEE Conference on Decision and Control 1986 - Athens, Greece Duration: 10 Dec 1986 → 12 Dec 2010 Conference number: 25th https://ieeexplore.ieee.org/xpl/conhome/4048689/proceeding

Conference

Conference	IEEE Conference on Decision and Control 1986
Country/Territory	Greece
City	Athens
Period	10/12/86 → 12/12/10
Internet address	https://ieeexplore.ieee.org/xpl/conhome/4048689/proceeding

Access to Document

10.1109/cdc.1986.267301

Cite this

@inproceedings{b0c1d04dca094a69b1d34e2eb787ca60,

title = "Adaptive robust control (convergence, stability and performance)",

abstract = "The authors show that a robust adaptive controller can be developed which stabilizes all members of a wide class of systems. The class of systems includes those having significant unmodeled dynamics and nonminimum phase characteristics. The theoretical results are supported by experimental evidence of the claimed robustness properties. The success of the algorithm is a result of the amalgamation of various techniques including regression vector filtering, pole assignment, estimator deadzone, least squares and internal model principle.",

author = "Goodwin, {Graham C.} and Hill, {David J.} and Mayne, {David Q.} and Middleton, {Richard H.}",

year = "1986",

doi = "10.1109/cdc.1986.267301",

language = "English",

pages = "468--473",

booktitle = "1986 25th IEEE Conference on Decision and Control",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE Conference on Decision and Control 1986 ; Conference date: 10-12-1986 Through 12-12-2010",

url = "https://ieeexplore.ieee.org/xpl/conhome/4048689/proceeding",

}

TY - GEN

T1 - Adaptive robust control (convergence, stability and performance)

AU - Goodwin, Graham C.

AU - Hill, David J.

AU - Mayne, David Q.

AU - Middleton, Richard H.

N1 - Conference code: 25th

PY - 1986

Y1 - 1986

N2 - The authors show that a robust adaptive controller can be developed which stabilizes all members of a wide class of systems. The class of systems includes those having significant unmodeled dynamics and nonminimum phase characteristics. The theoretical results are supported by experimental evidence of the claimed robustness properties. The success of the algorithm is a result of the amalgamation of various techniques including regression vector filtering, pole assignment, estimator deadzone, least squares and internal model principle.

AB - The authors show that a robust adaptive controller can be developed which stabilizes all members of a wide class of systems. The class of systems includes those having significant unmodeled dynamics and nonminimum phase characteristics. The theoretical results are supported by experimental evidence of the claimed robustness properties. The success of the algorithm is a result of the amalgamation of various techniques including regression vector filtering, pole assignment, estimator deadzone, least squares and internal model principle.

UR - http://www.scopus.com/inward/record.url?scp=0022984837&partnerID=8YFLogxK

U2 - 10.1109/cdc.1986.267301

DO - 10.1109/cdc.1986.267301

M3 - Conference Paper

AN - SCOPUS:0022984837

SP - 468

EP - 473

BT - 1986 25th IEEE Conference on Decision and Control

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE Conference on Decision and Control 1986

Y2 - 10 December 1986 through 12 December 2010

ER -

Adaptive robust control (convergence, stability and performance)

Abstract

Conference

Access to Document

Other files and links

Cite this