DocumentCode
1503915
Title
Advanced automation concepts for large-scale systems
Author
Berkan, R.C. ; Upadhyaya, B.R. ; Tsoukalas, L.H. ; Kisner, R.A. ; Bywater, R.L.
Author_Institution
Dept. of Nucl. Eng., Tennessee Univ., Knoxville, TN, USA
Volume
11
Issue
6
fYear
1991
Firstpage
4
Lastpage
12
Abstract
An automatic control system for large-scale systems that integrates methods in artificial intelligence, signal processing, and nonlinear control to provide fast and efficient diagnostics and reliable control is presented. The integrated system reduces the procedural load and facilitates the operator tasks by creating a condensed representation of plant status. Operator tasks are emulated by building computer-based algorithms which validate sensor signals, strategies, commands, and performance tracking and which generate reliable decisions and control actions. The advanced concepts on which the system is based are discussed. Also discussed are fault tolerance, signal and command validation, nonlinear control, and the system executive module. An application of the integrated control system to the Experimental Breeder Reactor-II (EBR-II) is described. The simulation results show that the advanced concepts yield efficient control strategies, including reactor control during startup.<>
Keywords
computerised signal processing; knowledge based systems; large-scale systems; nonlinear control systems; nuclear power stations; power station computer control; EBR-II; Experimental Breeder Reactor-II; artificial intelligence; automatic control system; command validation; fault tolerance; large-scale systems; nonlinear control; signal; signal processing; system executive module; validation; Artificial intelligence; Automatic control; Automation; Control systems; Intelligent sensors; Large-scale systems; Nonlinear control systems; Process control; Signal generators; Signal processing algorithms;
fLanguage
English
Journal_Title
Control Systems, IEEE
Publisher
ieee
ISSN
1066-033X
Type
jour
DOI
10.1109/37.92985
Filename
92985
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