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Estimation and Optimal Feedback Control Theory Applied to a Nuclear Boiling Water Reactor

B. Frogner, Lawrence M. Grossman

Open publisher page 18 citations

Abstract

A linear dynamic model, a quadratic performance index, and a Gaussian stochastic noise assumption (LQG-theory) have been used to design a feedback controller for a simulated current design 1100-MW(e) boiling water reactor. The total plant power control is studied in the range of 65 to 100% of rated power, with main emphasis on load-following control. An extended Kalman filter used in parallel with the compensator during normal operation is suggested for on-line parameter estimation. The algorithms are considered suitable for implementation in direct digital control.

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What this paper is about

A linear dynamic model, a quadratic performance index, and a Gaussian stochastic noise assumption (LQG-theory) have been used to design a feedback controller for a simulated current design 1100-MW(e) boiling water reactor. The total plant power control is studied in the range of 65 to 100% of rated power, with main emphasis on load-following control. An extended Kalman filter used in parallel with the compensator during normal operation is suggested for on-line parameter estimation. The algorithms are considered suitable for implementation in direct digital control.

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OpenAlex reports 18 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A linear dynamic model, a quadratic performance index, and a Gaussian stochastic noise assumption (LQG-theory) have been used to design a feedback controller for a simulated current design 1100-MW(e) boiling water reactor. The total plant power control is studied in the range of 65 to 100% of rated power, with main emphasis on load-following control. An extended Kalman filter used in parallel with the compensator during normal operation is suggested for on-line parameter estimation. The algorithms are considered suitable for implementation in direct digital control.

Key concepts: Linear-quadratic-Gaussian control, Control theory (sociology), Boiling water reactor, Kalman filter, Controller (irrigation), Boiling, Range (aeronautics), Optimal control

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