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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication15th European Workshop on Advanced Control and Diagnosis, ACD 2019
PublisherSpringer
Publication statusAccepted for publication - 15 Sep 2019
Event15th European Workshop on Advanced Control and Diagnosis - Bologna, Italy
Duration: 21 Nov 201922 Nov 2019

Publication series

NameLecture Notes in Control and Information Sciences
PublisherSpringer
ISSN (Print)0170-8643
ISSN (Electronic)2522-5383

Workshop

Workshop15th European Workshop on Advanced Control and Diagnosis
Abbreviated titleACD 2019
Country/TerritoryItaly
CityBologna
Period21/11/1922/11/19

Keywords

  • MPC
  • multi-resolution
  • nuclear reactor
  • PWR
  • subspace identification
  • wavelet

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