A multivariate adaptive regression B-spline algorithm (BMARS) for solving a class of nonlinear optimal feedback control problems

S. Richardson; Song Wang; Leslie Jennings

doi:10.1016/j.automatica.2007.09.001

A multivariate adaptive regression B-spline algorithm (BMARS) for solving a class of nonlinear optimal feedback control problems

S. Richardson, Song Wang, Leslie Jennings

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

In this paper we present a novel method for solving a class of nonlinear optimal feedback control problems with moderately high dimensional state spaces, based on an adapted version of the BMARS algorithm. Numerical experiments were performed using problems with up to six state variables. The numerical results clearly demonstrate the efficiency and potential of the method for solving high dimensional problems. (c) 2007 Elsevier Ltd. All rights reserved.

Original language	English
Pages (from-to)	1149-1155
Journal	Automatica
Volume	44
Issue number	4
DOIs	https://doi.org/10.1016/j.automatica.2007.09.001
Publication status	Published - 2008

Access to Document

10.1016/j.automatica.2007.09.001

Cite this

@article{60968b22a414477a8c123f1e27c47454,

title = "A multivariate adaptive regression B-spline algorithm (BMARS) for solving a class of nonlinear optimal feedback control problems",

abstract = "In this paper we present a novel method for solving a class of nonlinear optimal feedback control problems with moderately high dimensional state spaces, based on an adapted version of the BMARS algorithm. Numerical experiments were performed using problems with up to six state variables. The numerical results clearly demonstrate the efficiency and potential of the method for solving high dimensional problems. (c) 2007 Elsevier Ltd. All rights reserved.",

author = "S. Richardson and Song Wang and Leslie Jennings",

year = "2008",

doi = "10.1016/j.automatica.2007.09.001",

language = "English",

volume = "44",

pages = "1149--1155",

journal = "Automatica",

issn = "0005-1098",

publisher = "Elsevier",

number = "4",

}

TY - JOUR

T1 - A multivariate adaptive regression B-spline algorithm (BMARS) for solving a class of nonlinear optimal feedback control problems

AU - Richardson, S.

AU - Wang, Song

AU - Jennings, Leslie

PY - 2008

Y1 - 2008

N2 - In this paper we present a novel method for solving a class of nonlinear optimal feedback control problems with moderately high dimensional state spaces, based on an adapted version of the BMARS algorithm. Numerical experiments were performed using problems with up to six state variables. The numerical results clearly demonstrate the efficiency and potential of the method for solving high dimensional problems. (c) 2007 Elsevier Ltd. All rights reserved.

AB - In this paper we present a novel method for solving a class of nonlinear optimal feedback control problems with moderately high dimensional state spaces, based on an adapted version of the BMARS algorithm. Numerical experiments were performed using problems with up to six state variables. The numerical results clearly demonstrate the efficiency and potential of the method for solving high dimensional problems. (c) 2007 Elsevier Ltd. All rights reserved.

U2 - 10.1016/j.automatica.2007.09.001

DO - 10.1016/j.automatica.2007.09.001

M3 - Article

SN - 0005-1098

VL - 44

SP - 1149

EP - 1155

JO - Automatica

JF - Automatica

IS - 4

ER -

A multivariate adaptive regression B-spline algorithm (BMARS) for solving a class of nonlinear optimal feedback control problems

Abstract

Access to Document

Fingerprint

Cite this