Wavelet-based model predictive control of PWR nuclear reactor using multi-scale subspace identification

Vineet Vajpayee; Victor Becerra; Nils Bausch; Jiamei  Deng

Wavelet-based model predictive control of PWR nuclear reactor using multi-scale subspace identification

Vineet Vajpayee^*, Victor Becerra, Nils Bausch, Jiamei Deng

^*Corresponding author for this work

School of Energy & Electronic Engineering

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

Abstract

This work presents multi-scale model predictive control design scheme employing wavelet basis function. The proposed scheme is established upon multi-scale subspace identification technique. It is aimed to utilize the proficiency of wavelets in multi-scale data projection and the robustness of subspace identification during estimation in a model predictive control set-up. The multi-scale state-space models estimated at different scales are used for output prediction and for designing predictive control strategy. The competence of the proposed approach is established for constrained load-following problem of a pressurized water-type nuclear reactor. In addition, the fault-tolerant capability of the control algorithm is also tested.

Original language	English
Title of host publication	15th European Workshop on Advanced Control and Diagnosis, ACD 2019
Publisher	Springer
Publication status	Accepted for publication - 15 Sep 2019
Event	15th European Workshop on Advanced Control and Diagnosis - Bologna, Italy Duration: 21 Nov 2019 → 22 Nov 2019

Publication series

Name	Lecture Notes in Control and Information Sciences
Publisher	Springer
ISSN (Print)	0170-8643
ISSN (Electronic)	2522-5383

Workshop

Workshop	15th European Workshop on Advanced Control and Diagnosis
Abbreviated title	ACD 2019
Country/Territory	Italy
City	Bologna
Period	21/11/19 → 22/11/19

Keywords

MPC
multi-resolution
nuclear reactor
PWR
subspace identification
wavelet

Embargoed Document

VV_ACD_2019
Accepted author manuscript (Post-print), 1.1 MB
Due to publisher’s copyright restrictions, this document is not freely available to download from this website until: 1/01/50

1 Finished

Fault Tolerant Control for Increased Safety and Security of Nuclear Power Plants
Becerra, V. & Bausch, N.
Engineering and Physical Sciences Research Council
1/12/18 → 28/02/22
Project: Research

Cite this

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title = "Wavelet-based model predictive control of PWR nuclear reactor using multi-scale subspace identification",

abstract = "This work presents multi-scale model predictive control design scheme employing wavelet basis function. The proposed scheme is established upon multi-scale subspace identification technique. It is aimed to utilize the proficiency of wavelets in multi-scale data projection and the robustness of subspace identification during estimation in a model predictive control set-up. The multi-scale state-space models estimated at different scales are used for output prediction and for designing predictive control strategy. The competence of the proposed approach is established for constrained load-following problem of a pressurized water-type nuclear reactor. In addition, the fault-tolerant capability of the control algorithm is also tested.",

keywords = "MPC, multi-resolution, nuclear reactor, PWR, subspace identification, wavelet",

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day = "15",

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Vajpayee, V, Becerra, V , Bausch, N & Deng, J 2019, Wavelet-based model predictive control of PWR nuclear reactor using multi-scale subspace identification. in 15th European Workshop on Advanced Control and Diagnosis, ACD 2019. Lecture Notes in Control and Information Sciences, Springer, 15th European Workshop on Advanced Control and Diagnosis, Bologna, Italy, 21/11/19.

Wavelet-based model predictive control of PWR nuclear reactor using multi-scale subspace identification. / Vajpayee, Vineet; Becerra, Victor ; Bausch, Nils; Deng, Jiamei .

15th European Workshop on Advanced Control and Diagnosis, ACD 2019. Springer, 2019. (Lecture Notes in Control and Information Sciences).

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

TY - GEN

T1 - Wavelet-based model predictive control of PWR nuclear reactor using multi-scale subspace identification

AU - Vajpayee, Vineet

AU - Becerra, Victor

AU - Bausch, Nils

AU - Deng, Jiamei

N1 - 12 months embargo. Springer. This is a post-peer-review, pre-copyedit version of an article published in [insert journal title]. The final authenticated version is available online at: http://dx.doi.org/[insert DOI]

PY - 2019/9/15

Y1 - 2019/9/15

N2 - This work presents multi-scale model predictive control design scheme employing wavelet basis function. The proposed scheme is established upon multi-scale subspace identification technique. It is aimed to utilize the proficiency of wavelets in multi-scale data projection and the robustness of subspace identification during estimation in a model predictive control set-up. The multi-scale state-space models estimated at different scales are used for output prediction and for designing predictive control strategy. The competence of the proposed approach is established for constrained load-following problem of a pressurized water-type nuclear reactor. In addition, the fault-tolerant capability of the control algorithm is also tested.

AB - This work presents multi-scale model predictive control design scheme employing wavelet basis function. The proposed scheme is established upon multi-scale subspace identification technique. It is aimed to utilize the proficiency of wavelets in multi-scale data projection and the robustness of subspace identification during estimation in a model predictive control set-up. The multi-scale state-space models estimated at different scales are used for output prediction and for designing predictive control strategy. The competence of the proposed approach is established for constrained load-following problem of a pressurized water-type nuclear reactor. In addition, the fault-tolerant capability of the control algorithm is also tested.

KW - MPC

KW - multi-resolution

KW - nuclear reactor

KW - PWR

KW - subspace identification

KW - wavelet

UR - https://www.springer.com/series/642

M3 - Conference contribution

T3 - Lecture Notes in Control and Information Sciences

BT - 15th European Workshop on Advanced Control and Diagnosis, ACD 2019

PB - Springer

T2 - 15th European Workshop on Advanced Control and Diagnosis

Y2 - 21 November 2019 through 22 November 2019

ER -

Wavelet-based model predictive control of PWR nuclear reactor using multi-scale subspace identification

Abstract

Publication series

Workshop

Keywords

Embargoed Document

Fingerprint

Projects

Fault Tolerant Control for Increased Safety and Security of Nuclear Power Plants

Cite this