Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating

Mario A. Santillo; Matthew S. Holzel; Jesse B. Hoagg; Dennis S. Bernstein

doi:10.1109/CDC.2009.5400822

Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating

Mario A. Santillo, Matthew S. Holzel, Jesse B. Hoagg, Dennis S. Bernstein

Mechanical and Aerospace Engineering

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

6 Scopus citations

Abstract

We present a discrete-time adaptive control law that is effective for systems that are MIMO and either minimum phase or nonminimum phase. The adaptive control algorithm provides guidelines concerning the modeling information needed for implementation. This information includes a sufficient number of Markov parameters to capture the sign of the high-frequency gain as well as the nonminimum-phase zeros. No additional information about the poles or zeros need be known. In this paper, recursive least-squares estimation is used for concurrent Markov parameter estimation. We present numerical examples to illustrate the algorithm's effectiveness in handling nonminimum-phase zeros as plant changes occur.

Original language	English
Title of host publication	Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Pages	3466-3471
Number of pages	6
DOIs	https://doi.org/10.1109/CDC.2009.5400822
State	Published - 2009
Event	48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China Duration: Dec 15 2009 → Dec 18 2009

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Country/Territory	China
City	Shanghai
Period	12/15/09 → 12/18/09

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Access to Document

10.1109/CDC.2009.5400822

Cite this

Santillo, M. A., Holzel, M. S., Hoagg, J. B., & Bernstein, D. S. (2009). Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating. In Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 (pp. 3466-3471). Article 5400822 (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2009.5400822

Santillo, Mario A. ; Holzel, Matthew S. ; Hoagg, Jesse B. et al. / Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating. Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. 2009. pp. 3466-3471 (Proceedings of the IEEE Conference on Decision and Control).

@inproceedings{cf289e0dcbb4489a9fdd34471ac93221,

title = "Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating",

abstract = "We present a discrete-time adaptive control law that is effective for systems that are MIMO and either minimum phase or nonminimum phase. The adaptive control algorithm provides guidelines concerning the modeling information needed for implementation. This information includes a sufficient number of Markov parameters to capture the sign of the high-frequency gain as well as the nonminimum-phase zeros. No additional information about the poles or zeros need be known. In this paper, recursive least-squares estimation is used for concurrent Markov parameter estimation. We present numerical examples to illustrate the algorithm's effectiveness in handling nonminimum-phase zeros as plant changes occur.",

author = "Santillo, {Mario A.} and Holzel, {Matthew S.} and Hoagg, {Jesse B.} and Bernstein, {Dennis S.}",

year = "2009",

doi = "10.1109/CDC.2009.5400822",

language = "English",

isbn = "9781424438716",

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

pages = "3466--3471",

booktitle = "Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009",

note = "48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 ; Conference date: 15-12-2009 Through 18-12-2009",

}

Santillo, MA, Holzel, MS, Hoagg, JB & Bernstein, DS 2009, Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating. in Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009., 5400822, Proceedings of the IEEE Conference on Decision and Control, pp. 3466-3471, 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009, Shanghai, China, 12/15/09. https://doi.org/10.1109/CDC.2009.5400822

Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating. / Santillo, Mario A.; Holzel, Matthew S.; Hoagg, Jesse B. et al.
Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. 2009. p. 3466-3471 5400822 (Proceedings of the IEEE Conference on Decision and Control).

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

TY - GEN

T1 - Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating

AU - Santillo, Mario A.

AU - Holzel, Matthew S.

AU - Hoagg, Jesse B.

AU - Bernstein, Dennis S.

PY - 2009

Y1 - 2009

N2 - We present a discrete-time adaptive control law that is effective for systems that are MIMO and either minimum phase or nonminimum phase. The adaptive control algorithm provides guidelines concerning the modeling information needed for implementation. This information includes a sufficient number of Markov parameters to capture the sign of the high-frequency gain as well as the nonminimum-phase zeros. No additional information about the poles or zeros need be known. In this paper, recursive least-squares estimation is used for concurrent Markov parameter estimation. We present numerical examples to illustrate the algorithm's effectiveness in handling nonminimum-phase zeros as plant changes occur.

AB - We present a discrete-time adaptive control law that is effective for systems that are MIMO and either minimum phase or nonminimum phase. The adaptive control algorithm provides guidelines concerning the modeling information needed for implementation. This information includes a sufficient number of Markov parameters to capture the sign of the high-frequency gain as well as the nonminimum-phase zeros. No additional information about the poles or zeros need be known. In this paper, recursive least-squares estimation is used for concurrent Markov parameter estimation. We present numerical examples to illustrate the algorithm's effectiveness in handling nonminimum-phase zeros as plant changes occur.

UR - http://www.scopus.com/inward/record.url?scp=77950826876&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77950826876&partnerID=8YFLogxK

U2 - 10.1109/CDC.2009.5400822

DO - 10.1109/CDC.2009.5400822

M3 - Conference contribution

AN - SCOPUS:77950826876

SN - 9781424438716

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 3466

EP - 3471

BT - Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009

T2 - 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009

Y2 - 15 December 2009 through 18 December 2009

ER -

Santillo MA, Holzel MS, Hoagg JB, Bernstein DS. Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating. In Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. 2009. p. 3466-3471. 5400822. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC.2009.5400822

Adaptive control using retrospective cost optimization with RLS-based estimation for concurrent Markov-parameter updating

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this