Application of fuzzy logic for power change rate constraint in core power control at Reaktor TRIGA PUSPATI

The 1MWth Reaktor TRIGA PUSPATI (RTP) in Malaysia Nuclear Agency has been in operation more than 37 years. The existing core power control uses a conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output stable and operate within t...

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Bibliographic Details
Published inIOP conference series. Materials Science and Engineering Vol. 785; no. 1; pp. 12022 - 12039
Main Authors Minhat, Mohd Sabri, Mohd Subha, Nurul Adilla, Hassan, Fazilah, Ahmad, Anita
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.04.2020
Subjects
Actuation
Algorithms
Control algorithms
Control rods
Control theory
Controllers
Feedback control
Fuzzy control
Fuzzy logic
Hydraulic models
Mathematical analysis
Mathematical models
Nuclear reactors
Nuclear safety
Power control
Tracking control
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Summary:The 1MWth Reaktor TRIGA PUSPATI (RTP) in Malaysia Nuclear Agency has been in operation more than 37 years. The existing core power control uses a conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output stable and operate within the acceptable error bands for the safety demand of the RTP. At present, the power tracking performance of the system could be considered unsatisfactory where constant gains of power change rate constraint and control rod speed constraint are used. Hence, a study of a new power change rate constraint design to achieve safe control rod speed range is conducted to improve the current performance. In this paper, a new power change rate constraint (PCRC) method using fuzzy logic is proposed to control the core power. The Takagi-Sugeno (T-S) type Fuzzy model is chosen due to its capability to work well with linear controller and making the computational control algorithm efficient. The model for core power control consists of mathematical models of the reactor core, FCA, and control rods selection algorithm. The mathematical models of the reactor core are based on point kinetics model, thermal-hydraulic models and reactivity models. The performance of power tracking and actuation signal for control rod drive input are compared between the conventional PCRC (cPCRC) and Fuzzy PCRC using MATLAB. In conclusion, the proposed Fuzzy PCRC has satisfactory performance in core power tracking for controlling the nuclear reactor with high reliability and safety.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/785/1/012022