dc.contributor.author |
Olivier, Laurentz Eugene
|
|
dc.contributor.author |
Craig, Ian Keith
|
|
dc.date.accessioned |
2017-03-24T09:16:23Z |
|
dc.date.issued |
2016-07 |
|
dc.description.abstract |
A fault-tolerant nonlinear model predictive controller (FT-NMPC) is presented in this paper. State
estimates, required by the NMPC, are generated with the use of a particle filter. Faults are identiced with the nonlinear
generalized likelihood ratio method (NL-GLR), for which a bank of particle filters is used to generate the required fault
innovations and covariance matrices. A simulated grinding mill circuit serves as the platform for illustrating the use of
this fault detection and isolation (FDI) scheme along with the NMPC. The results indicate that faults can be correctly
identiced and compensated for in the NMPC framework to achieve optimal performance in the presence of faults. |
en_ZA |
dc.description.department |
Electrical, Electronic and Computer Engineering |
en_ZA |
dc.description.embargo |
2017-07-31 |
|
dc.description.librarian |
hb2017 |
en_ZA |
dc.description.sponsorship |
National Research Foundation of South Africa (Grant Number 90533). |
en_ZA |
dc.description.uri |
https://www.journals.elsevier.com/ifac-papersonline |
en_ZA |
dc.identifier.citation |
Olivier, LE & Craig, IK 2016, 'Fault-tolerant nonlinear MPC using particle filtering', IFAC-PapersOnLine, vol. 49, no. 7, pp. 177-182. |
en_ZA |
dc.identifier.issn |
1474-6670 |
|
dc.identifier.other |
10.1016/j.ifacol.2016.07.242 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/59523 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
Elsevier |
en_ZA |
dc.rights |
© 2016 IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in IFAC papers online. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in IFAC papers online, vol. 49, no. 7, pp. 177-182, 2016. doi : 10.1016/j.ifacol.2016.07.242. |
en_ZA |
dc.subject |
Generalized likelihood ratio |
en_ZA |
dc.subject |
Particle filter |
en_ZA |
dc.subject |
Fault-tolerant nonlinear model predictive controller (FT-NMPC) |
en_ZA |
dc.subject |
Nonlinear model predictive controller (NMPC) |
en_ZA |
dc.subject |
Fault detection and isolation (FDI) |
en_ZA |
dc.subject |
Model predictive control (MPC) |
en_ZA |
dc.title |
Fault-tolerant nonlinear MPC using particle filtering |
en_ZA |
dc.type |
Postprint Article |
en_ZA |