Parameter convergence in the stochastic gradient adaptive control law

Sheng-Fuu Lin; P. R. Kumar

doi:10.1109/CDC.1988.194513

Parameter convergence in the stochastic gradient adaptive control law

Sheng-Fuu Lin^*, P. R. Kumar

^*Corresponding author for this work

National Chiao Tung University

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

The authors exhibit self-tuning results for the adaptive control law proposed by G.C. Godwin, P.J. Ramadge and P.E. Caines (SIAM J. Control Optim., vol. 19, no. 6, pp. 829-853, 1981). They also show how the dimension of the adaptive control law can be reduced in situations where the reference trajectory has a low order of excitation. The results are compared with an adaptive control law proposed by P.R. Kumar and L. Praly (SIAM J. Control Optim., vol. 25, no. 4, pp. 1053-1071, 1987).

Original language	English
Pages (from-to)	1211-1212
Number of pages	2
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/CDC.1988.194513
State	Published - 1 Dec 1988
Event	Proceedings of the 27th IEEE Conference on Decision and Control - Austin, TX, USA Duration: 7 Dec 1988 → 9 Dec 1988

Access to Document

10.1109/CDC.1988.194513

Fingerprint Dive into the research topics of 'Parameter convergence in the stochastic gradient adaptive control law'. Together they form a unique fingerprint.

Cite this

@article{9187aec1c78640e895930f3555db6e60,

title = "Parameter convergence in the stochastic gradient adaptive control law",

abstract = "The authors exhibit self-tuning results for the adaptive control law proposed by G.C. Godwin, P.J. Ramadge and P.E. Caines (SIAM J. Control Optim., vol. 19, no. 6, pp. 829-853, 1981). They also show how the dimension of the adaptive control law can be reduced in situations where the reference trajectory has a low order of excitation. The results are compared with an adaptive control law proposed by P.R. Kumar and L. Praly (SIAM J. Control Optim., vol. 25, no. 4, pp. 1053-1071, 1987).",

author = "Sheng-Fuu Lin and Kumar, {P. R.}",

year = "1988",

month = dec,

day = "1",

doi = "10.1109/CDC.1988.194513",

language = "English",

pages = "1211--1212",

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

issn = "0191-2216",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "null ; Conference date: 07-12-1988 Through 09-12-1988",

}

TY - JOUR

T1 - Parameter convergence in the stochastic gradient adaptive control law

AU - Lin, Sheng-Fuu

AU - Kumar, P. R.

PY - 1988/12/1

Y1 - 1988/12/1

N2 - The authors exhibit self-tuning results for the adaptive control law proposed by G.C. Godwin, P.J. Ramadge and P.E. Caines (SIAM J. Control Optim., vol. 19, no. 6, pp. 829-853, 1981). They also show how the dimension of the adaptive control law can be reduced in situations where the reference trajectory has a low order of excitation. The results are compared with an adaptive control law proposed by P.R. Kumar and L. Praly (SIAM J. Control Optim., vol. 25, no. 4, pp. 1053-1071, 1987).

AB - The authors exhibit self-tuning results for the adaptive control law proposed by G.C. Godwin, P.J. Ramadge and P.E. Caines (SIAM J. Control Optim., vol. 19, no. 6, pp. 829-853, 1981). They also show how the dimension of the adaptive control law can be reduced in situations where the reference trajectory has a low order of excitation. The results are compared with an adaptive control law proposed by P.R. Kumar and L. Praly (SIAM J. Control Optim., vol. 25, no. 4, pp. 1053-1071, 1987).

UR - http://www.scopus.com/inward/record.url?scp=0024172204&partnerID=8YFLogxK

U2 - 10.1109/CDC.1988.194513

DO - 10.1109/CDC.1988.194513

M3 - Conference article

AN - SCOPUS:0024172204

SP - 1211

EP - 1212

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

SN - 0191-2216

Y2 - 7 December 1988 through 9 December 1988

ER -